Introduction to Spatial Planning

This chapter provides the conceptual foundation for understanding spatial prioritisation for both conservation and multiple-use planning. We begin with the rationale for spatial planning, introduce systematic approaches, explain how mathematical optimisation is used, and explore modern advances including climate-smart planning, multiple-use zoning, and ecosystem services.

Why Spatial Planning?

The world’s ecosystems face unprecedented pressures from competing human demands. Habitat loss, overexploitation, pollution, invasive species, and climate change threaten biodiversity and the ecosystem services upon which human societies depend. Simultaneously, growing global demands for food, energy, minerals, infrastructure and water intensify competition for limited space (Neubert et al. 2025).

Marine environments, in particular, face growing demands from fishing, shipping, aquaculture, renewable energy, mining, and tourism—all competing for the same ocean space. Spatial planning offers a pathway to address these dual challenges by:

Protecting biodiversity: Identifying and safeguarding areas critical for species survival, migration, reproduction, and genetic diversity
Maintaining ecosystem services: Ensuring continued provision of services such as carbon sequestration, coastal protection, fisheries production, and water filtration
Supporting sustainable development: Allocating space for fishing, aquaculture, renewable energy, and other economic activities in suitable locations
Managing multiple uses: Balancing competing demands on limited space by allocating areas to different activities based on their compatibility, value, and sustainability
Minimising conflicts: Reducing use-use conflicts by spatially separating incompatible activities or identifying areas where co-location is possible
Achieving policy commitments: Meeting national and international targets such as the Kunming-Montreal Global Biodiversity Framework’s goal of protecting 30% of land and sea by 2030, while supporting Sustainable Development Goals for economic growth and food security
Building resilience: Designing spatial plans that can withstand and adapt to climate change and evolving socioeconomic conditions

Without deliberate spatial planning, development and resource use tend to follow economic opportunity rather than ecological need. The result is often fragmented habitats, depleted populations, and degraded ecosystem services. Spatial planning provides a framework for making informed, transparent decisions about where to focus conservation efforts and how to allocate space among competing uses.

The Conservation Challenge

Protected areas remain a cornerstone of conservation strategy. However, simply designating more protected areas is not sufficient. We must ensure that protected areas:

Represent all ecosystems: Not just spectacular or accessible areas, but the full range of habitats and species
Are large enough: Providing sufficient area for viable populations and ecological processes
Are connected: Allowing species movement, gene flow, and climate adaptation
Persist over time: With adequate management and enforcement
Complement other management: Working alongside sustainable use and restoration efforts
Consider multiple uses: Acknowledge that there are a range of pressures on our ecosystems that require managed access.

Achieving these goals requires moving beyond ad hoc decisions to systematic, evidence-based planning.

What is Spatial Prioritisation?

Spatial prioritisation is the process of identifying where actions should be located to most efficiently achieve specified objectives. Given limited resources and competing demands for space, it is impossible to do everything, everywhere. Spatial prioritisation tools help decision-makers strategically allocate space and investments.

The fundamental questions in spatial prioritisation depend on the planning context:

For conservation planning:

Which areas should be protected to achieve biodiversity targets at minimum cost?

For sector allocation in multiple-use planning:

Where should fishing, aquaculture, energy infrastructure, and protected areas be located to balance ecological, economic, and social objectives?

For zoning:

How do we allocate planning units to different management zones (e.g., no-take reserves, sustainable fishing areas, aquaculture zones) to achieve multiple objectives simultaneously?

The Need for Systematic Approaches

Traditional approaches to spatial planning often relied on:

Ad hoc decisions: Reacting to immediate pressures rather than strategic allocation
Single-sector focus: Optimising for one use without considering others
Expert opinion alone: Lacking transparent, repeatable methods
Opportunistic selection: Protecting or allocating areas based on availability rather than strategic value

For conservation planning specifically, ad hoc approaches led to:

Inefficient use of resources: Protecting areas that contribute little to overall conservation goals
Gaps in representation: Failing to include areas important for less well-known species or habitats
Conflict with other uses: Not accounting for economic or social costs
Lack of transparency: Difficulty explaining or justifying decisions to stakeholders

For multiple-use planning, ad hoc approaches resulted in:

Use-use conflicts: Fishing gear damaged by energy infrastructure, shipping disrupting whale migration
Suboptimal economic returns: High-value activities excluded from most suitable areas
Environmental degradation: Cumulative, unmanaged impacts from overlapping uses
Social inequity: Industrial uses displacing small-scale fishers and traditional users

Systematic conservation planning (Margules and Pressey 2000) and multiple-use spatial planning (Neubert et al. 2025) address these limitations by using quantitative methods to identify priority areas based on explicit objectives and constraints.

Key Concepts

Planning Units

The planning region is divided into discrete spatial units called planning units. These can be:

Regular grids (squares or hexagons)
Existing administrative boundaries
Ecological units (e.g., watersheds, habitat patches)

Each planning unit can be either selected (included in the spatial plan) or not selected. In zoning problems, planning units are allocated to different management zones rather than simply selected or not. The goal of prioritisation is to determine which planning units to select (or which zone to allocate them to).

Features

Features are the spatial elements of interest in the planning region. Depending on planning objectives, features can include:

Species distributions (e.g., coral reef fish, seabirds, threatened species)
Habitat types (e.g., seagrass beds, mangroves, coral reefs, spawning grounds)
Depth zones (e.g., continental shelf, bathyal, abyssal)
Geomorphological features (e.g., seamounts, ridges, canyons)
Fisheries productivity (catch per unit area, spawning grounds, nursery habitats)
Aquaculture suitability (temperature, depth, water quality, suitable sites)
Renewable energy potential (wind speed, wave energy, tidal currents, solar radiation)
Tourism value (scenic beauty, dive sites, wildlife viewing areas)
Accessibility (distance to ports, proximity to markets, shipping routes)
Ecosystem services (carbon storage, coastal protection, fisheries production, water filtration)
Traditional use areas (subsistence fishing, cultural sites, community resources)
Conflict zones (areas where multiple uses overlap or compete)

Each feature has a spatial distribution across planning units. In conservation planning, features are elements to protect, and high feature values indicate high conservation priority. In multiple-use planning, features can represent suitability for different activities—high values might indicate where fishing, aquaculture, or energy generation would be most productive.

Targets

Targets specify how much of each feature should be represented in the spatial plan. Targets can be expressed as:

Absolute targets: A specific amount (e.g., 1000 km² of seagrass habitat, 500 MW of wind energy capacity)
Relative targets: A percentage of the total (e.g., 30% of each habitat type, 20% of high-productivity fishing grounds allocated to no-take reserves)

Setting appropriate targets is a critical step that should be informed by:

Science: Population viability requirements, minimum patch sizes, ecosystem thresholds
Policy: International commitments (e.g., 30x30), national legislation, regional agreements
Stakeholder input: Sectoral needs, community priorities, equity considerations

Cost

Cost represents the expense or difficulty of including each planning unit in the spatial plan. Cost can include:

Financial costs: Land/sea acquisition, management expenses
Opportunity costs: Foregone economic benefits (e.g., fishing revenue, agricultural production)
Social costs: Displacement of communities or livelihoods
Proxy costs: Distance from shore (as a surrogate for enforcement difficulty)
Sectoral costs: Lost revenue to fishing, aquaculture, or tourism from area restrictions
Infrastructure costs: Installation expenses for renewable energy, cable laying, port development
Conflict costs: Incompatibility between uses (e.g., bottom trawling damages aquaculture gear)
Environmental costs: Habitat damage, bycatch, pollution, carbon emissions

When no specific cost data are available, equal area cost assigns the same cost to each planning unit, effectively minimising the total area selected. Note that in multiple-use planning with zoning, different zones may have different cost structures, reflecting the varying implications of allocating areas to different management regimes.

Constraints

Constraints are rules that must be satisfied by any valid solution:

Locked-in constraints: Planning units that must be selected (e.g., existing protected areas)
Locked-out constraints: Planning units that cannot be selected (e.g., shipping lanes, urban areas)

Objective Functions

The objective function defines what the prioritisation algorithm is trying to achieve. Different objectives suit different planning contexts:

Minimum Set Objective

The classic conservation planning objective:

Find the smallest set of planning units (lowest total cost) that meets all representation targets.

This is ideal when targets are well-established and the goal is to minimise resources (cost) required to achieve them. This objective is also applicable in multiple-use contexts—for example, identifying the minimum area needed for aquaculture to meet food security targets while minimising conflict with other sectors.

Minimum Shortfall Objective

When budgets are fixed:

Given a fixed budget, find the set of planning units that minimises the total shortfall from achieving targets across all features.

This is useful when resources are limited and you want to make progress towards all targets rather than fully achieving some whilst ignoring others. In multiple-use planning, the “budget” might represent the total area available for a particular sector, or a financial constraint on development.

Other Objectives

The prioritizr package supports additional objectives including:

Maximum coverage: Maximise representation of features within a fixed budget
- Use case: Maximise biodiversity representation within 30% area budget
- Use case: Maximise wind energy generation within 500 km² allocation
Maximum utility: Maximise the weighted sum of features represented
- Use case: Prioritise high-value species or high-productivity fishing areas
Minimum largest shortfall: Minimise the worst-case shortfall for any single feature
- Use case: Ensure no single species or sector is disproportionately impacted

Mathematical Optimisation

The Integer Linear Programming Approach

Modern spatial prioritisation uses integer linear programming (ILP) to find optimal solutions. Unlike heuristic approaches (such as simulated annealing used in Marxan), ILP solvers are guaranteed to find the globally optimal solution.

The prioritizr R package (Hanson et al. 2025) provides a flexible interface for building and solving conservation planning problems using ILP. It supports multiple commercial and open-source solvers including:

Gurobi (commercial, fastest for large problems)
IBM CPLEX (commercial)
HiGHS (open-source, recommended default)
CBC (open-source)

Advantages Over Heuristic Methods

Aspect	ILP (prioritizr)	Heuristics (Marxan)
Optimality	Guaranteed optimal	Near-optimal
Speed	Often faster	Variable
Reproducibility	Deterministic	Stochastic
Flexibility	Highly flexible	More constrained

Climate-Smart Spatial Planning

Climate change poses fundamental challenges to both conservation and multiple-use planning. Species distributions are shifting, habitats are degrading, and historical baselines may no longer represent future conditions. Simultaneously, climate change affects the productivity and suitability of areas for human uses such as fisheries and aquaculture. Climate-smart spatial planning explicitly incorporates climate change considerations into prioritisation to ensure plans remain effective under future conditions (Buenafe et al. 2025).

Why Climate-Smart Planning Matters

Traditional spatial planning assumes that features remain static within planning units. However:

For biodiversity:

Species are shifting their ranges poleward and to deeper waters
Coral reefs and other habitats are experiencing mass mortality events
Ocean temperatures, chemistry, and currents are changing
Protected area networks designed for today’s distributions may become ineffective as species move

For economic activities:

Fisheries productivity is shifting with changing ocean conditions
Aquaculture suitability is changing (temperature, oxygen, disease risk)
Extreme weather events threaten infrastructure (ports, offshore installations)
Traditional fishing grounds may become less productive or shift location

Climate-smart planning ensures that spatial allocations—whether for conservation or economic use—remain viable and effective under future climate scenarios. Climate-smart planning can be implemented through several approaches but in shinyplanr, users can select climate layers that preferentially weight refugia areas.

Climate refugia are areas that are expected to experience less climate change impact and may serve as safe havens for biodiversity. These can be identified using:

Projected temperature anomalies
Climate velocity (the speed at which conditions shift spatially)
Habitat stability metrics
Ensemble model projections

Given uncertainty in climate projections, robust planning aims to find solutions that perform well across multiple climate scenarios rather than optimising for a single projection.

Multiple-Use Spatial Planning

Conservation does not occur in isolation. Marine and terrestrial environments support multiple human activities including fishing, shipping, tourism, renewable energy, aquaculture, and extractive industries. Rather than viewing conservation and resource use as competing objectives, multiple-use spatial planning seeks to balance biodiversity protection with sustainable economic activities, creating spatial plans where sectors coexist or are strategically separated based on compatibility (Neubert et al. 2025).

The Marine Context

Marine environments are particularly suited to multiple-use planning due to their three-dimensional structure and the potential for compatible activities to co-locate. However, they also face intense competition for space:

Growing demands include:

Food security: Expanding commercial and artisanal fisheries, aquaculture development
Energy transition: Offshore wind farms, wave energy, tidal energy installations
Economic development: Shipping lanes, ports, submarine cables, potential seabed mining
Tourism and recreation: Diving, whale watching, recreational fishing, coastal tourism
Conservation: Marine protected areas, species recovery programs, ecosystem restoration
Traditional uses: Subsistence fishing, cultural sites, indigenous rights and territories

The Challenge of Multiple Objectives

Different stakeholder groups have competing but often legitimate objectives:

Conservation sector: Maximise biodiversity protection, achieve 30x30 targets
Fishing industry: Maintain access to productive fishing grounds, sustain catch levels
Aquaculture: Secure suitable sites for expansion, disease management zones
Renewable energy: Achieve climate targets through offshore wind and other installations
Tourism: Provide access to attractive areas for wildlife viewing and recreational activities
Shipping: Maintain efficient transport routes, minimise transit times and costs
Local communities: Preserve cultural sites, subsistence uses, traditional rights

These objectives often conflict—an area optimal for conservation may also be:

The most productive fishing ground
The best location for wind farms (high energy potential)
A critical shipping route
An important tourism destination

Multiple-use planning addresses these conflicts through systematic allocation that balances ecological, economic, and social goals.

Approaches to Multiple-Use Optimisation

Following Neubert et al. (2025), there are four main approaches to incorporating multiple uses in spatial optimisation:

1. Composite Costs

Aggregate multiple uses into a single cost metric that the optimisation minimises while meeting conservation targets.

Example: Cost = 0.4 × fishing_effort + 0.4 × aquaculture_suitability + 0.2 × shipping_density

Advantages: Simple, computationally efficient, easy to communicate

Limitations: Can obscure sector-specific impacts, sensitive to weighting choices

2. Constraints

Set sector-specific budget limits or exclude certain areas from consideration.

Example: Meet conservation targets while ensuring fishing revenue loss < $5M, and locking out shipping lanes

Advantages: Each sector considered separately, more control over impacts

Limitations: Requires detailed sector-specific data, harder to communicate

3. Zoning

Allocate planning units to different management zones with distinct objectives.

Example zones:

No-take marine reserve: Biodiversity protection, research
Sustainable fishing zone: Managed fishing, no bottom trawling
Aquaculture zone: Fish farming, shellfish cultivation
Renewable energy zone: Wind farms with compatible uses
General use zone: Multiple compatible activities

Advantages: Sectoral clarity, reduces conflicts, widely used in practice

Limitations: Requires substantial data, complex to configure, high computational demands

4. Multi-objective Optimisation

Simultaneously optimise multiple objective functions (e.g., maximise conservation AND maximise fishing value).

Advantages: Comprehensive trade-off analysis, flexible

Limitations: Very complex, requires advanced expertise, not yet widely accessible

shinyplanr primarily uses approaches 1 and 2 (composite costs and constraints), with approach 3 (zoning) possible through custom configuration of prioritizr. Approach 4 (multi-objective optimisation) is not currently implemented but represents a future development direction.

Zoning in Detail

Zoning is one of the most accessible and widely-used methods for multiple-use planning. Rather than binary selection (protect vs. don’t protect), zoning assigns each planning unit to a management zone with specific allowed and prohibited uses.

Key benefits:

Clarity: Each sector knows where they can and cannot operate
Conflict reduction: Incompatible uses are spatially separated
Flexibility: Different levels of protection and use intensity
Stakeholder buy-in: All sectors get designated areas

Compatible uses that can coexist in the same zone:

Offshore wind + no-take marine reserves (turbine foundations can act as artificial reefs)
Sustainable fishing + tourism (recreational diving, charter fishing)
Aquaculture + some fishing methods (if spatially managed to avoid gear conflicts)

Incompatible uses that should be separated:

Bottom trawling + aquaculture (gear conflicts, habitat disturbance)
Shipping lanes + offshore wind farms (collision risk)
No-take reserves + extractive fishing activities

The prioritizr package supports sophisticated zoning through its zones functionality. Each zone can have distinct features, targets, costs, and constraints, allowing simultaneous optimisation across all zones to find the best overall allocation.

Balancing Trade-offs

Multiple-use planning requires explicit consideration of trade-offs:

Identifying stakeholder objectives: What does each sector want to achieve?
Mapping activities: Where do different uses currently occur or could occur?
Quantifying impacts: How do uses affect each other and biodiversity?
Assessing compatibility: Which uses can coexist? Which conflict?
Exploring scenarios: What happens under different allocation schemes?
Evaluating equity: Who benefits? Who bears costs? Is the distribution fair?
Negotiating solutions: Finding compromises acceptable to stakeholders

shinyplanr supports exploring these trade-offs by allowing users to:

Use different cost layers representing sectoral impacts (fishing effort, aquaculture displacement, shipping density)
Apply constraints limiting impacts on specific sectors (budget constraints, locked-out areas)
Lock out areas with infrastructure or incompatible uses (shipping lanes, existing installations)
Compare scenarios with different configurations side-by-side
Visualise how parameter changes affect different stakeholder groups
Download results for further analysis and stakeholder engagement

Data for Multiple-Use Planning

Understanding current and potential ocean uses requires spatial data on human activities:

Fishing effort by gear type (trawl, longline, purse seine, artisanal)
Catch and revenue per area
Aquaculture sites and suitability maps
Potential mining areas and mineral deposits
Shipping vessel density and routes
Ports and anchorage areas
Submarine cables and pipelines
Existing offshore structures
Wind speed and consistency
Wave energy potential
Tidal currents
Bathymetry and seabed conditions
Dive sites and visitor numbers
Whale watching areas and seasonality
Recreational fishing effort
Coastal access points
Subsistence fishing areas
Cultural heritage sites
Indigenous marine territories
Community resource use patterns

Ecosystem Services

Ecosystem services are the benefits that humans derive from ecosystems. Incorporating ecosystem services into spatial planning allows conservation to contribute to human well-being alongside biodiversity protection (Dabalà et al. 2023).

Categories of Ecosystem Services

Provisioning services: Products obtained from ecosystems
- Fisheries production
- Timber and fibre
- Fresh water
- Genetic resources
Regulating services: Benefits from ecosystem processes
- Carbon sequestration and storage
- Coastal protection from storms and erosion
- Water purification
- Climate regulation
Cultural services: Non-material benefits
- Recreation and tourism
- Spiritual and religious values
- Aesthetic appreciation
- Educational value
Supporting services: Necessary for other services
- Nutrient cycling
- Primary production
- Habitat provision

Quantifying Ecosystem Services

Ecosystem services can be represented spatially through:

Biophysical models: Carbon stocks, fish biomass, coastal protection capacity
Economic valuation: Dollar value of services per area (e.g., fisheries production value, carbon sequestration value, tourism revenue)
Indicator species: Presence of species associated with services (e.g., commercial fish species, pollinator species)
Habitat proxies: Area of habitat types known to provide services (e.g., mangroves for coastal protection and carbon storage, seagrass for fisheries nurseries, coral reefs for tourism and biodiversity)

By including ecosystem service layers in prioritisation, planners can identify areas that simultaneously protect biodiversity and maximise benefits to human communities. For example, protecting mangrove ecosystems can deliver multiple services: carbon storage, coastal protection from storms and erosion, critical nursery habitat for fisheries, and biodiversity conservation (Dabalà et al. 2023). This multi-benefit approach strengthens the case for conservation by demonstrating tangible value to stakeholders.

Summary

Modern spatial prioritisation for conservation and multiple-use planning combines:

Systematic methods that are transparent, repeatable, and efficient
Mathematical optimisation that guarantees optimal solutions
Climate-smart approaches that account for changing conditions and future uncertainty
Multiple-use perspectives that balance conservation with sustainable economic activities
Ecosystem services that connect ecological function to human well-being
Stakeholder engagement that ensures equitable and legitimate planning processes

shinyplanr brings these capabilities to stakeholders through an accessible web interface. Whether you are designing protected area networks, planning marine spatial allocations, or exploring trade-offs between conservation and development, shinyplanr provides the tools for systematic, evidence-based spatial planning.

The Using shinyplanr vignette explains how to use shinyplanr to explore spatial planning scenarios, and the Setting Up vignette explains how to set up shinyplanr for new regions.