Exploring Future Scenarios of Rural Land Use Change

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Exploring Future Scenarios of Rural Land Use
Change

• Daniel Rutledge
• Environmental Defence Society
• Conflict in Paradise Conference
• 11-12 June 2008

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Acknowledgements

• Environmental Defence Society
• Landcare Research
• Alison Collins, Allan Hewitt, Anne-Gaelle
  Ausseil, Andrew Fenemor, Bob Frame,Bruce Burns,
  Craig Briggs, Craig Trotter, Graham Sparling,
  Jeremy Gabe, John Dymond, John Innes, John Scott,
  Maureen Mara, Mike Krausse, Niels Hoffmann, Penny
  Nelson, Richard Gordon, Robert Gibb, Susan Walker
• Robbie Combinatorial Price
• University of Waikato Louis Schipper, Myk
  Cameron, Jacques Poot
• NIWA Graham McBride, Sandy Elliott, Andrew Tait,
  Ross Woods
• Environment Waikato Beat Huser, Derek Phyn
• AgResearch Liz Wedderburn, Bruce Small
• Market Economics Garry McDonald
• Alchemists Ltd Tony Fenton
• Homefront Susanna Rutledge, Bugs, Daffy

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Objectives

• Introduce how we explore the future
• Simple statistics on rural land use trends
• Present highlights from several projects using
  scenarios to explore differentaspects of rural
  land use change

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Exploring the Future Process
Step 5 Explorepossible futures
Step 3 Understand past changes trends
Step 4Identify key drivers trends and
model possible future scenarios
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Rural Land UseA Simple Model
SOME IMPORTANT QUESTIONS
How big and where are land use stocks? What are
their associated practices?
How is land use changing where, i.e. flows?
What drives various changes?
What are the cultural, economic, environmental
social consequences?
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How good is our collective knowledge of land use,
practice, and change?
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Current Land UseStock Estimate
In play.Available for current future primary
production.
PRODUCTION67.5
CONSERVATION 31
Underestimate 1-2. Does not include local
council data.
RESIDENTIAL COMMERCIAL INDUSTRIAL 1
RURALRESIDENTIAL 0.5
Land Use Class
Production
Conservation
Stock estimates based on Agribase Land
Cover Database v2 (LCDB2) Protected Areas
Network NZ (PAN-NZ)
Urban
Rural Residential
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Land Use Flow Estimates
Tenure Review To Crown Estate 11,500 ha/yr
Urbanisation 550 4,500 ha/yr
Private Covenants 25,000 ha/yr
?
RESIDENTIAL COMMERCIAL INDUSTRIAL 1
RURALRESIDENTIAL 0.5
PRODUCTION 67.5
CONSERVATION 31
Conversions 140,000 ha/yr
Tenure Review To Freehold 12,600 ha/yr
Courtesy of Susan Walker, Landcare Research
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Tenure ReviewConservation Outcomes
Most in Needof Protection
Least in Needof Protection
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NZ Land UseConsequences of Urbanisation
All Blacks
Best
Super 14
Worst
Assumes 20 years
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Rural Land Use Trends Summary

• Production
• Net outflow of land to urban and conservation
• Urbanisation seems to disproportionately affect
  our best lands soils
• Conservation
• Net inflows of land from production
• Conservation outcomes may not be as good as they
  could be (controversial)
• Land use practices
• Not addressed too hard!
• Lots of good things happening but hard to get our
  heads around it.
• Data not very good!
• Take Home Message increasing
  population increasing needs, wants,
  expectations decreasing production
  base leading to

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Now were readyto talk about the future
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Key Drivers to 2100
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Exploring Coastal Environments

• DOC LCR project to support review of National
  Coastal Policy Statement
• Develop scenarios to evaluate condition of
  terrestrial coastal environments

• Results
• Condition (Remaining Native Land Cover)
• National 48
• Scenario 1 54 (better)
• Scenarios 2-5 31-43 (worse)
• Remaining Native Land Cover Protected
• National 62
• Scenarios 34-44 (all worse)
• Conclusions
• Coastal environments in worse condition
• More vulnerable to future development
• More susceptible to future biodiversity loss

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Exploring Climate Change Mitigation

• Context
• Manawatu Region Sustainable Land Use Initiative
  following 2004 storm
• Prepare whole farm plans to identify and properly
  manage highly erodible lands (HEL)

• Scenario
• Convert HEL on first 500 priority farms to
  plantation forestry
• Estimate co-benefits
• Sedimentation
• GHG emissions
• C storage from plantation forestry

Slides courtesy ofAnne-Gaelle Ausseil, Landcare
Research
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HEL Farms Co-Benefits
-36
- 47
-27
-50
Greenhouse Gas Emissions
Erosion
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HEL Farms Carbon Sequestration
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Catchment Land Use for Environmental
Sustainability
CLUES
Harris Consulting
Slides courtesy of Graham McBride, NIWA
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CLUES Exploring Land Use Impacts on Water
Quality Economics

• Explores impacts of land use land use change on
  nutrient loads (P N)
• Integrates several biophysical models an
  economic model
• Estimates nutrient loadings economics/employment
  on selected (sub)catchments based on land use

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CLUES Process
1) Select Catchment
2) Create scenarios
SingleTerminalReach
Multiple Reaches
5) Compare scenarios
3) Modify land use
4) Display results
e.g., Yield Map (load/area)
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150 tons/year N
75 tons/year N
Example of Outputs
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IDEASIntegrated Dynamic Environmental Assessment
System
Slides courtesy of John Dymond and Tim Davie,
Landcare Research
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IDEAS Exploring IntegratedCatchment Management

• Part of Motueka ICM Programme
• Integrated Modeling
• Land-Freshwater-Marine-Economic-Social
• Triple Bottom Line Indicators Economic-Environme
  ntal-Social
• Embedded in a collaborative learning framework
• Strong research networks
• Strong council networks
• Strong community networks

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IDEAS SCENARIOS
Natural
Intensive BMP
Present BMP
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Agricultural Job Numbers
Gross Economic Output - /yr
Low Flow Rate Max Water Take (m3/s)
Net N Yield to Marine (kg / yr)
But wait!
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Potential Effect on Aquacultureof Increased N
Yields
Estimatedfutureproductioncapacity.
Current production capacity.
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Choosing Regional Futures
Developing and applyingplanning tools to make
informed choices for the future
OBJECTIVE 2 Spatial decision support system
development
OBJECTIVE 1 Improved communication
deliberation tools
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SDSSSystem Design
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3 Scenarios for Waikatos Future2001-2050 based
on SDSS Prototype
Dairy Expansion
Diversification
Village Life
Land for dairying increases 4 annually
Demand for non-dairy primaryproduction land
increases
Residential land increases 7-fold
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Summary

• Futures research and scenarios help us think more
  constructively about the future
• They help us make decisions they do not provide
  solutions.
• Understanding and (spatially-explicit) modelling
  of land use land use change and its
  consequences for rural landscapesis now gaining
  momentum
• Rural Landscapes
• Conflicts arising from competing demands will
  only intensify over time
• How to produce more with less land? Technology to
  the rescue?
• How best to decide amongst those competing uses?
  Who decides?
• Better futures requires better information!
• We need better information about land use
• Better includes quantity (targeted), quality,
  and accessibility
• But balance between public good private
  opportunity? Confidentiality?
• Ultimately hidden/inaccessible data is the same
  as no data.

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The best way to predict the future is to create
it. Peter Drucker