MarxanMarxan and terrestrial and terrestrial conservation planningconservation planning

An example from western NSW

Jessica Sushinsky, Richard Fuller, Michael Drielsma, James Watson, Robert Taylor, Jill Smith, and Hugh Possingham

MarxanMarxan analysisanalysis

Define the problem

Plan the analysis

Gather and process data

Planning units

Conservation features Conservation features

Cost, clumping, targets, etc.

Interpret and apply results

The problemThe problem

Woodlands subject to heavy clearing.

Declines in biodiversity

How do we restore and protect biodiversity?protect biodiversity?

Limited budget, data, options, and time

Report commissioned by NSW Department of Environment, Climate Change and Water (DECC)

Biodiversity Research and Management DivisionNSW National Parks and Wildlife Service

The regionThe region

Western Woodlands Way (WWW)

75,425 km2

located in the sheep-wheat belt of north western NSWwestern NSW

Region is a mix of conservation reserves, agricultural land, and small urban areas.

The planThe plan

Develop a large scale conservation plan that will allow for the recovery and persistence of woodland-dependent species in WWW.

Increase extent of woodland habitat for Increase extent of woodland habitat for threatened, woodland-dependent species.

Increase connectivity across the landscape.

Use Marxan to identify the best areas for restoration effort in WWW.

Planning unitsPlanning units

Based on a cadastral map (2006) of all properties within WWW.

Set status of planning Set status of planning units according to objectives.

Result was 3582 planning units available for selection.

Conservation featuresConservation features

40 woodland-dependent species.

Point location data from the Atlas of New South Wales Wildlife (provided by DECC).

Created current and historic Created current and historic species distribution models. Using the modelling software Maxent

Historic distributions gave an estimate of how suitable cleared land would be if it was restored. Used to calculate amount in the puvsspr2 input file

CostCost

Cost assigned to each planning unit was the cost of restoration.

Restoration cost based on rateable based on rateable value of the land.

Cost acquisition data layer developed by Carwardine, et al.

cost per planning unit

ClumpingClumping

Increasing connectivity across the landscape was one of our main objectives.

Used Boundary Length Modifier (BLM) to control clumping

Higher BLM means a more compact Higher BLM means a more compact reserve system.

Tested a range of BLMs to decide which to apply.

Boundary Length Modifier

ResultsResults

The best solution included1402 properties. 11,379km2

All but 2 species met their target area.their target area.

Concentration of properties in north. Connecting existing habitat.

Some selected properties already covered by native woodland.

ApplicationApplication

Data summaries for each CMA. Implementation at this level.

First phase of a large, multipart analysis.

Properties selected Properties selected subject to a fine scale analysis. Metapopulation models.

Implementation will involve working with land owners. Re-run Marxan with new PU status data.

LessonsLessons

Marxan is flexible and can be used in some creative ways.

Marxan is a powerful tool but the context of the problem is important.

Establish and stick to objectives

The best solution isnt the end point it should be analysed further and applied in context.