Habitat suitability based landscape optimization vs. expert rules in agricultural landscapes Lutz Tischendorf Elutis Modelling & Consulting Inc. January 26, 2007 in association with O2 Planning + Design Inc.

Outline – Scope and Context January 26, 2007  NAESI  Study Area  General Approach  Landscape Optimization  Case Study  Results  Conclusions Elutis Modelling & Consulting Inc.

NAESI January 26, 2007 National Agricultural Environmental Standards Initiative Elutis Modelling & Consulting Inc.  Develop standards to reduce negative effects of Agriculture on: Air, Water, Soil, Biodiversity  Identify quantitative targets for evaluating performance of standards

NAESI - Biodiversity January 26, 2007 Elutis Modelling & Consulting Inc. Tasks:  Develop Habitat based Biodiversity Standards  Identify Habitat based Biodiversity Targets

Study Area January 26, 2007 Elutis Modelling & Consulting Inc.

Study Area January 26, 2007 Elutis Modelling & Consulting Inc.

Study Area January 26, 2007 Elutis Modelling & Consulting Inc.

Study Area January 26, 2007 Elutis Modelling & Consulting Inc.

General Approach January 26, 2007 Elutis Modelling & Consulting Inc. Landscape Optimization Landcover Data HSI Models Surrogate Species Selection Objective Constraints Customized Software Habitat based Biodiversity Standards + Target

Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. Change Analyze Objective: (e.g. measurable biodiversity target) Expert input, Scenario: - transition rules - constraints did target value improve? reject landcover conversions and use previous landscape again accept landcover conversions and continue maximum number of runs or generations completed? Stop yes no Typical Feedback Loop of Heuristic Approaches

Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc.

Case Study January 26, 2007 Elutis Modelling & Consulting Inc. Objective: Identify a potential biodiversity target as the best possible landscape configuration under consideration of:  conflicting species’ habitat requirements and  socio-economic constraints 2 Approaches:  Expert Rules  Landscape Optimization using Genetic Algorithms

Case Study January 26, 2007 Elutis Modelling & Consulting Inc. What would/could this landscape look like, if it would provide optimal habitat suitability for 4 selected surrogate species with 50% less cropland?

Case Study – Expert Rules January 26, 2007 Elutis Modelling & Consulting Inc. 1.Retain large patches (>10 ha) within the landscape, and any portions of large patches (>800 ha) 2.Retain corridors and stepping stones across the landscape, Maintain inter- patch distances and stepping stone sizes appropriate to dispersing species 3.Build concentric management buffer zones around wetlands so that 10 m surrounding each wetland is unmanaged cover 4.Create large patches of natural vegetation and untilled cover. In this case, the large patches chosen were areas of wetlands complexes (defined as wetlands within 200 m of each other) that would benefit from the conversion of the intervening arable agricultural land to permanent cover and natural grasslands 5.Protect quarter-sections with >25% badlands and saline flats 6.Riparian buffers of 60 m on all streams 7.Riparian corridors of 100 m on >3rd order rivers 8.Riparian corridors of at least 150 m along significant landscape connections 9.Buffer grassland patches to leave adjacent areas within 200 m in open vegetation (no tree or shrub plantings)

Case Study – Expert Rules January 26, 2007 Elutis Modelling & Consulting Inc. Current Landscape

Case Study – Expert Rules January 26, 2007 Elutis Modelling & Consulting Inc. Expert Landscape

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. 1.Data Preparations:  intersect current landscape with Quarter Sections  create 120 m buffer polygons around water and wetland  exclude areas with high irrigation potential 2.Transition Rules:  A cropland polygon could be transformed into grassland, pasture or hay/forage  A transformed grassland polygon could be changed back into cropland, pasture or hay/forage  A pasture polygon could be transformed into grassland, cropland or hay/forage  A hay/forage polygon could be transformed into grassland, pasture or cropland  A cropland buffer polygon around water or wetland could be transformed into shrub.  A pasture buffer polygon around water or wetland could be transformed into shrub.  A hay/forage buffer polygon around water or wetland could be transformed into shrub.  A transformed shrub buffer polygon could be changed back to cropland buffer, pasture buffer, hay/forage buffer or grassland. 3.Set Socio-economic Constraints:  keep 150,000 ha (22%) cropland  do not convert cropland in areas with highest irrigation potential

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. 3.Chose Surrogate Species: Grey Copper Loggerhead Shrike Northern Pintail Swift Fox  3 taxonomic groups  home ranges 6 ha – 1080 ha

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. 4.Habitat Suitability Models:  Grey Copper (6ha home range, wetland + hay/forage)  Loggerhead Shrike (64 ha home range, shrub + grassland + no slope)  Northern Pintail (650 ha home range, grassland + wetland)  Swift Fox (1080 ha home range, grassland on even ground)

Case Study - Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. Change Analyze 2. Transition Rules did target value improve? reject landcover conversions and use previous landscape again accept landcover conversions and continue maximum number of runs or generations completed? Stop yes no Genetic Algorithm 1. Data Preparation 3. Constraints 4. Calculate HSI for 4 surrogate species

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Quantitative Measures:  Average Habitat Suitability Index  Habitat amount Qualitative Results:  Habitat Suitability Maps  Generalized Landcover Map – Optimized Landscape

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. Current Landscape

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. Optimized Landscape

Case Study – Landscape Optimization January 26, 2007 Elutis Modelling & Consulting Inc. Optimized Landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Improvement during Optimization

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Improvement after Optimization

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Amount Increase after Optimization

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Maps – Grey Copper (6ha home range) current landscape optimized landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Maps – Loggerhead Shrike (64 ha home range) current landscape optimized landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Maps – Northern Pintail (650 ha home range) current landscape optimized landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Maps – Swift Fox (1080 ha home range) current landscape optimized landscape

Case Study – Results: Expert vs. Optimization January 26, 2007 Elutis Modelling & Consulting Inc. expert landscape optimized landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Suitability Improvement in Expert and Optimized Landscape

Case Study – Results January 26, 2007 Elutis Modelling & Consulting Inc. Habitat Amount Increase in Expert and Optimized Landscape

Conclusions January 26, 2007 Elutis Modelling & Consulting Inc. Initial Tasks: Develop Habitat based Biodiversity Standards  maintain landscape heterogeneity at different spatial scales  habitat is not just “green stuff”  consider all of one or multiple species’ relevant landcover types when assessing habitat based biodiversity Identify Habitat based Biodiversity Targets  optimal landscape represents a potential reference condition, benchmark or biodiversity target under consideration of: conflicting habitat requirements habitat evaluation at different spatial scales socio-economic constraints

Conclusions January 26, 2007 Elutis Modelling & Consulting Inc.  landscape heterogeneity at different spatial scales is important  habitat for a species is usually composed of more than just one natural landcover type  species operate at different spatial scales, which must be considered in biodiversity standards  landscape optimization has the potential to reveal optimal landscape composition and configuration for best possible suitability and amount of habitat for multiple surrogate target  landscape optimization does not reveal whether habitat amount and configuration is “enough” or “optimal” for population viability  effects of corridors, stepping stones and connectivity in general on population viability can only be explored by optimizing a landscape for population viability rather than habitat suitability  habitat suitability patterns in optimal landscapes can enhance expert rules  landscape optimization produced a landscape scenario with results superior to those obtained from expert rules in enhancing existing and creating new habitat for a set of target species

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Selection Protocol: represent most important ecosystem/cover types respond to important agricultural stressors are primarily area- and dispersal-limited are habitat specialists and generalists have different home range scales have different life-cycle lengths represent keystone species represent terrestrial/aquatic interface represent a sufficiently large suite of taxonomic groups Elutis Modelling & Consulting January 26, 2007