Three Essays on Conservation : Sahan T. M. Dissanayake
Dissertation Proposal Defense
Department of Agricultural & Consumer Economics
University of Illinois
June 17th 2010 Three Essays on Conservation Outline : Outline 2 Introduction
Amenity Driven Price Effects and Dynamic Reserve Design
Results and Next Steps
A Choice Experiment of Preference for Grassland Habitat Restoration
The Next Steps
Spatial Reserve Design within Military Lands
Section 1: Methods and Results
Section 2: Methods and Results
Section 3: Methods and Results
The Next steps
Conclusion Motivation : Motivation 3 Why do we care? Globally intact ecosystems are being converted at over 1% per year. Only about 50% of the forest area that existed at the time of the rise of agriculture remain. Increasing conversion of undeveloped habitat to human dominated landscapes. Motivation : Motivation 4 Why do we care? Over the past few hundred years, humans have increased the species extinction rate by as much as 1,000 times over background rates. More than half of the areas of six out of fourteen terrestrial biomes have been converted. Habitat loss and fragmentation is a primary cause of extinction. Motivation : Motivation 5 What can we do? Identify the optimal land area to be set aside as protected reserves. Ideally all natural biodiversity should be protected. Resources available for conservation are limited. Therefore But Ecological and spatial aspects Species presence
Size and Shape
Clustering Economic considerations
Consumer preferences Chapter Summaries : Chapter Summaries 6 The first chapter extends dynamic reserve design models by presenting a model that incorporates location based amenity price effects.
The second chapter contributes to the non-market valuation and conservation literature by using a choice experiment survey to analyze the willingness to pay and preferences for grassland restoration.
The third chapter contributes to the reserve design and conservation literature by presenting spatial reserve design models to allocate land for conservation given alternative land use. Chapter One : Chapter One 7 Amenity Driven Price Effects in Conservation Reserve Design: A Dynamic Linear Integer Programming Approach
Collaborators: Prof. Hayri Önal
General Problem Area: Conservation
Dynamic Reserve Design Chapter One: Literature Review : Chapter One: Literature Review 8 Given limited availability of conservation resources it is important to consider the optimum site selection to maximize conservation benefits.
Mathematical optimization models can be used to solve the optimum site selection problem.
Mathematical programming in reserve design begins in the late 1980’s with the pioneering work by Kirkpatrick (1983). Chapter One: Literature Review : Chapter One: Literature Review 9 The basic site selection model OR Maximize the number of species populations that can be protected under a conservation budget Select a minimum number of habitat sites that collectively contain a specified number of species populations But such models result in
dispersed reserve configurations. Chapter One: Literature Review : Chapter One: Literature Review 10 Base Model Scattered Sites Chapter One: Literature Review : Chapter One: Literature Review 11 Most of these recent reserve design models are static. Static models assume Fixed availability of land Total availability of budget Fixed prices These are not realistic Land can get developed Funds are obtained over time Species distributions can vary Land prices can change Fixed distribution of species But Chapter One: Literature Review : Chapter One: Literature Review 12 The literature on dynamic reserve selection models is very recent.
Seminal paper by Costello and Polasky published in 2004.
Paper by Meir et al. on the importance of dynamic modeling published in 2004.
Dynamic Stochastic Programming (SDP).
Two-period integer optimization models.
Constrained Markov decision process and meta-population modeling.
Many heuristic solutions.
Highest irreplaceability/Highest species richness. Chapter One: Literature Review : Chapter One: Literature Review 13 Dynamic Stochastic Programming (SDP) is computationally complex and the problem size increases exponentially in the number of parcels (Costello and Polasky 2004, Strange et al. 2004, Meir et al. 2004)
Costello and Polasky 2004 applied the model to 10 parcels and 6 periods.
Difficult to include spatial and ecological criteria. Chapter One: Literature Review : Chapter One: Literature Review 14 Two-Period integer optimization model with expected values is a computationally easy solution and provides results that are near optimal (Snyder et al. 2004)
Snyder 2004, uses a scenario optimization model that assigns to each site a 50% probability of being developed.
Randomness drives the results.
The model does not take spatial constraints or price effects into consideration.
None of the published dynamic reserve site selection formulations take price feedback effects into account. Chapter One: Research Question : Chapter One: Research Question 15 How can amenity driven price effects be incorporated into a reserve design model?
Does ignoring amenity driven prices effects lead to suboptimal reserves?
Does incorporating amenity driven price effects matter in an uncertain world? Chapter One: Key Results : Chapter One: Key Results 16 Created a modeling framework that can incorporate various aspects of dynamic reserve design models.
The dynamic model that incorporates amenity effects selects sites at a lower per-site cost.
This implies that conservation programs should avoid purchasing land in the same neighborhood over multiple time periods (concentrate on a particular area in a one period).
Though the two period model performs better for low levels of uncertainty as the uncertainty increases there is no significant advantage in accounting for amenity driven prices effects. Chapter One: Methods : Chapter One: Methods 17 We introduce a two-period linear integer programming model based on methods presented by Snyder et al. (2004).
The model imposes an exogenous price premium on endogenously selected sites (sites selected in the second period that are adjacent to sites selected in the first period).
The model allows for spatial and ecological criteria. Chapter One: Methods : Chapter One: Methods 18 We mention only the key constraints here
Second period budget constraint Base price Price premium Second period selections adjacent to first period selections Sites adjacent to first period selections Ak = 1 only if site k is selected in the second period and is adjacent to a first period selection Identify adjacency Chapter One: Results : Chapter One: Results 19 Results for Selecting Two Clusters Chapter One: Results : Chapter One: Results 20 Monte Carlo Simulation Results Chapter One: Results : Chapter One: Results 21 Monte Carlo Simulation Results Chapter One: Results : Chapter One: Results 22 Analysis of Results under Uncertainty Chapter One: Results and Future Steps : Chapter One: Results and Future Steps 23 Key Results
The dynamic model with location based amenity effects selects sites for conservation at a lower cost.
As uncertainty increases there is no gain in accounting for location based amenity price effects.
This implies that conservation programs should avoid purchasing land in the same neighborhood over multiple time periods.
Extend the framework to include endogenously determined development uncertainty.
Expand the model to include price effects due to supply and demand shifts. Chapter One: Acknowledgements : Chapter One: Acknowledgements 24 I express my gratitude
Hayri Önal, Richard Brazee, Philip Garcia, Carl Nelson, and Rhett Farrell,
Participants at the 2009 AAEA meeting,
Participants at the PERE workshop
Three anonymous referees
This research was partially supported by the ERDC-CERL project No.W81EWF-7204-6330 and the USDA National Institute of Food and Agriculture, Hatch Project No. ILLU 05-0361. Chapter Two : Chapter Two 25 Preferences for Grassland Habitat Restoration: Results from a Choice Experiment Survey
Collaborators: Prof. Amy W. Ando
General Problem Area: Conservation
Grassland Restoration Choice Experiments Chapter Two: Motivation : Chapter Two: Motivation 26 Grasslands are open land areas where grasses and various species of wildflowers are the main vegetation.
In North America there are three main types of grassland ecosystems. Chapter Two: Motivation : Chapter Two: Motivation 27 Illinois has lost 99.9% of its original prairie grassland Map of Historic Prairies in Illinois (1820)
(Anderson 1970) Map of Rural Grassland in Illinois (2000)
(Created from IDA Land Cover map) Chapter Two: Motivation : Chapter Two: Motivation 28 The loss of grasslands has led to the widespread and ongoing decline of bird populations that have affinities for grass-land and grass-shrub habitats.
An analysis of Breeding Bird Survey (BBS) routes between 1966 and 2002 showed that of 28 species of grassland specialists.
3 species increased significantly
17 species decreased significantly Dickcissels During the 25-year period ending in 1984, grassland songbirds (e.g., Henslow’s Sparrows, Grasshopper Sparrows, Savannah Sparrows, Bobolinks, Eastern and Western Meadowlarks, and Dickcissels) in Illinois declined by 75% - 95%. Chapter Two: Motivation : Chapter Two: Motivation 29 Widespread grassland restoration is the most effective way to restore bird populations (Vickery et al 1999)
Many grassland restoration initiatives
Schulenberg Prairie at the Morton Arboretum in Lisle, Illinois, 100 acres (40 hectares)
Around Fermilab in Bativia, Illinois, 455 acres (184 hectares)
Nachusa Grasslands, NE Illinois 2,826 acres (Dustin M. Ramsey © 2001) (www.nachusagrasslands.org) Chapter Two: Motivation : Chapter Two: Motivation 30 At the same time restoration ecologists have no guidance from the valuation literature about the preferences people have over the characteristics of restored grasslands.
The social value of restoration efforts would be increased if planners had knowledge about
the total social value from grassland restoration
presence of wildflowers,
use of management techniques such as prescribed burning Chapter Two: Research Question : Chapter Two: Research Question 31 Understand the consumers’ preferences and WTP for grassland restoration?
What is the tradeoff between species richness and population density in consumers’ preferences for habitat restoration?
How is the public’s WTP for habitat restoration affected by management options with negative externalities, such as the use of prescribed fire, and how does the disamenity change with distance from the restored area? Chapter Two: Literature Review : Chapter Two: Literature Review 32 There is a large literature on optimal protected area planning but most of that research uses production-side factors – the locations of endangered species, the cost of land, the threat posed to natural areas by development - to guide decisions about where to locate dedicated natural areas.
Ando and Shah (2010) show that conservation activity can yield higher social benefits if decision makers consider the preferences of people when they plan their network of natural areas. Chapter Two: Literature Review : Chapter Two: Literature Review 33 Much of the literature on estimating the value of habitat conservation and restoration has focused on
Wetland preservation and restoration (for a review see Boyer and Polasky 2004),
Forest preservation and restoration (forests in Finland by Lehtonen 2003, IJmeer Nature Reserve by Baarsma 2003),
The protection of individual endangered bird species (the Mexican Spotted Owl by Loomis and Ekstrand 1997,, and the Whooping Crane by Bowker and Stoll, 1988)
Recreation and hunting (recreation demand by Hanley et al. 2002, management of Moose populations by Horne and Petäjistö 2003, moose hunting by Boxall et al. 1996 and Salmon Fishery by Roe et al. 1996).
To date no economic valuation study has analyzed the preferences for grassland restoration. Chapter Two: Literature Review : Chapter Two: Literature Review 34 Species richness has been used to represent biodiversity in many ecological and protected areas selection studies.
There is a growing ecological literature that indicates that species richness is not indicative of biodiversity and functional diversity (Wilsey et al 2005, Chalcraft et al. 2008, Dickson and Wilsey 2009, and Flynn et al. 2009).
Loomis and Larson (1994) demonstrate that wildlife population density is an important variable affecting the public’s WTP for restoring habitats. Chapter Two: Literature Review : Chapter Two: Literature Review 35 There have been many restoration efforts for bird habitats but there are no existing choice experiment valuation studies on the public’s preferences for bird habitat restoration.
A CV study on preferences for urban green space in Montpellier, France indicates that respondents are willing to pay more when birds are present (Caula, 2009).
A CV study on preference for protecting or restoring native bird populations in Waikato, New Zealand estimated that the value of native bird conservation in the region at 13 million 2008 NZ$ (Kaval and Roskruge 2009). Chapter Two: Literature Review : Chapter Two: Literature Review 36 Naturally occurring periodic fires integral to the existence of grasslands (Vogl 1979).
Many grassland restoration efforts require management by fire and/or grazing to prevent woody succession and to eliminate invasive species (Vogl 1979, Copeland et al. 2002).
At the same time smoke and ash from prescribed burns can be hazardous to motorists and become a problem for local residents. Nachusa’s prescribed fire crew. Chapter Two: Methods : Chapter Two: Methods 37 Choice Experiment Surveys
Based on Lancaster’s (1966) consumer theory
Consumers derive utility not from goods themselves but rather from the attributes or characteristics that the goods posses.
Conjoint measurement: mathematical psychology
Conjoint analysis: marketing research
CE surveys allow the calculation of part worth utilities for attributes and therefore the calculation of tradeoffs between different attributes. Chapter Two: Methods : Chapter Two: Methods 38 In a typical CE survey the respondent repeatedly chooses the best option from several hypothetical choices that have varying values for important attributes.
We present respondents with opportunities to express preferences over pairs of hypothetical restored grasslands that have the following attributes:
wildlife population density
number of endangered species
frequency of using fire
distance to site
prevalence of wildflowers
cost Chapter Two: Methods : Chapter Two: Methods 39 Steps in conducting CE survey
Characterize the decision problem
Identify and describe the attributes
Develop an experimental design
Develop the questionnaire (Currently at this stage)
Interpret results for policy analysis or decision support Chapter Two: Methods : Chapter Two: Methods 40 Data Collection: Mail Survey
Stratified sample of Illinois residents (Obtained from the Survey Research Lab)
1$ incentive with the Survey Chapter Two: Methods : Chapter Two: Methods 41 Empirical design
CE surveys require experiment design techniques to identify a combination of attributes and levels to create the survey profile.
Experimental Design (3 attribute, 2 level example) Full factorial design Main effects for attribute A Interaction effects for attribute AB Chapter Two: Methods : Chapter Two: Methods 42 Empirical design
The proposed survey contains 7 attributes with 3 levels each.
A full factorial binary design will include 37*37 = 4,782,969 profiles.
We create a fractional factorial experiment design that will allow both main effects and interaction effects to be estimated.
The survey design is presented in Appendix A Profile Number Attribute Levels Attributes Chapter Two: Methods : Chapter Two: Methods 43 The Survey Instrument
We will create a block design where the 54 choice sets will be separated into blocks of 6 choice profiles, giving 9 unique surveys.
The final survey instrument will contain 6 sets of binary choice question sets followed by a small demographic questionnaire.
Appendix B contains the current version of the survey instrument. Chapter Two: Methods : Chapter Two: Methods 44 Model Estimation
CE survey’s are based on random utility theory (RUM) in which the utility consists of a systematic or deterministic component and a random, unobservable component.
Standard multinomial logit models has been used in estimating the results of many choice experiment surveys.
The standard multinomial logit models assume that respondents are homogeneous.
Therefore we use a mixed multinomial logit model (mixed logit, random parameter logit).
It is necessary to test for violations of the IIA assumption and if necessary a more complex model such as a nested logit model would need to be used for the estimation. Chapter Two: Methods : Chapter Two: Methods 45 Model Estimation
Assuming a linear utility, the utility gained by person q from alternative i in choice situation t is given by
The marginal rates of substitution between the attributes can be calculated using the coefficient for cost as a numeraire.
The ratios can be interpreted as average marginal WTP for a change in each attribute.
I was selected for the EAERE Summer School in Belpasso on biodiversity conservation and will be learn about estimating Choice Experiments. non-stochastic explanatory variables socio-economic characteristics intrinsic preference for the alternative heterogeneity of preferences IID and extreme value type I (Gumbel) Chapter Two: The Methods : Chapter Two: The Methods 46 Expected Results Chapter Two: Future Work : Chapter Two: Future Work 47 Simultaneously work on the survey and the estimation techniques.
Complete the survey and obtain IRB approval by the middle of July.
Focus groups by the middle of August.
Final IRB approval beginning of September.
Mail Surveys by middle of September.
Gather and input data by end of October.
Complete initial analysis by end of November. Chapter Two: Acknowledgements : Chapter Two: Acknowledgements 48 I express my gratitude to
Prof. Amy W. Ando, Prof. John Braden, Prof. Jeff Brawn and Prof. James Miller
Xiaolin Ren, Christina Jolejole and Catalina Londoño
Participants at the PERE workshop at the University of Illinois. Chapter Three : Chapter Three 49 Selection of Clustered Conservation Areas for Species Relocation, Multiple Species, and Multiple Land Use
Collaborators: Prof. Hayri Önal, Dr. James D. Westervelt, and
Dr. Harold E. Balbach
General Problem Area: Conservation
Spatial Reserve Design Multiple Land Use Chapter Three : Motivation : Chapter Three : Motivation 50 Conservation and the Military BLM DoD USFS FWS NPS Density of Species BLM DoD USFS FWS NPS Distribution of Species Percent Species # Species per 100,000 Hectares Suitable habitats for many endangered and imperiled species are located in DoD lands Chapter Three : Motivation : Chapter Three : Motivation 51 Conservation and the Military The DoD spends more per acre to manage species per year than any other federal
land management agency In 2006, the DoD spent $4.1 billion on the environment ($1.6 billion for restoration and conservation) Military prevents destructive urban and agricultural development within installations Chapter Three : Motivation : Chapter Three : Motivation 52 Increasing military needs
require more and more land Need effective utilization of land for both military and conservation goals Need to relocate species effected by expanding military training requirements Therefore Mathematical optimization models can design an optimum landscape that best addresses conservation needs given military training How? Existing reserve design formulations do not include the necessary spatial and joint management considerations But Chapter Three : Motivation : Chapter Three : Motivation 53 The current land allocation problem requires
Relocation and Movement Distances
Joint Management Considerations
Joint management of multiple species
Simultaneously identifying land for training and habitat Chapter Three : Research Question : Chapter Three : Research Question 54 Identify the optimal selection of sites for conservation given alternate (military) land use.
How can reserve design models be extended to incorporate
multiple conservation goals
multiple land use Chapter Three : Application 1 : Chapter Three : Application 1 55 Need to identify armor training areas and habitat areas to relocate GTs from areas of new development. Ft. Benning GA The installation covers 182,000 acres southeast of Columbus, GA
US Army Armor Center and School will be co-located to Ft. Benning
New firing ranges and maneuver areas
The new areas have populations of GT’s Chapter Three : Application 2 : Chapter Three : Application 2 56 Need to identify management areas for the joint management of GT and GF Ft. Stewart, GA The installation covers 280,000 acres in SE Georgia. Chapter Three : Literature Review : Chapter Three : Literature Review 57 We contribute to the reserve design literature but given that the selected areas will be within the boundaries of military installations where the primary goal is the military readiness we use the term Conservation Management Area (CMA) to refer to the selected areas. Chapter Three : Literature Review : Chapter Three : Literature Review 58 Clustered CMAs are obtained by identifying a center and minimizing the sum of the distance between the center and the other selected site. Chapter Three : Methods and Data : Chapter Three : Methods and Data 59 We develop six linear mixed-integer multi-objective programming models.
Base relocation model for Ft. Benning
Minimum distance relocation model for Ft. Benning
Meta-clustering relocation model for Ft. Benning
Clustered habitat selection model for Ft. Stewart
Multiple species habitat selection model for Ft. Stewart
Multiple land use model for Ft. Benning Chapter Three : Methods and Data : Chapter Three : Methods and Data 60 Chapter Three: Relocation Model : Chapter Three: Relocation Model 61 Relocation Model Clustering
Number of Clusters
Minimum cluster population
Maximum carrying capacity
Minimum total population Chapter Three: Relocation Model : Chapter Three: Relocation Model 62 Minimum Relocation Distance
Meta-Clustering 1 Constraint is only binding if both l and k are centers. Chapter Three: Relocation Model : Chapter Three: Relocation Model 63 Meta-Clustering II Meta-Clustering
Only one meta-cluster
Every cluster center is assigned to the meta-cluster Chapter Three: Relocation Model : Chapter Three: Relocation Model 64 Data
Figure 1: Current and future military training areas
Figure 2: Observed GT habitats and GT suitability Chapter Three: Relocation Model : Chapter Three: Relocation Model 65 Results Base relocation Minimum distance relocation minimum distance model places the CMAs centrally compared to the base model Chapter Three: Relocation Model : Chapter Three: Relocation Model 66 Results Meta-clustering Results The meta-clustering model clusters the CMAs
When the maximum distance is minimized to 15 cells the model selects one cluster Chapter Three: Joint Management Model : Chapter Three: Joint Management Model 67 Base Clustering Model Slide 68: 68 Data
Military training areas
Location of ponds Chapter Three: Joint Management Model Slide 69: 69 Results Base Model The base model selects clustered CMAs Chapter Three: Joint Management Model The joint management models selects CMAs located close to ponds Joint Management Model Chapter Three: Multiple Landuse Model : Chapter Three: Multiple Landuse Model 70 Budget constraint and cost minimization
Separate habitat and military clusters
Distance to Roads
we choose βmilitary >0 and βhabitat <0 Distance to the nearest road Cost minimizing Budget constrained Slide 71: 71 Data
Base area Roads
Habitat Suitability Military Suitability Chapter Three: Multiple Landuse Model Slide 72: 72 Results
For one CMA and two CMAs
With varying inter-CMA distance Chapter Three: Multiple Landuse Model Chapter Three: Results and Future Steps : Chapter Three: Results and Future Steps 73 Key Results
Spatial and joint management considerations can be included in reserve design models.
Military (and other federal?) land can be effectively used for conservation purposes without disrupting the primary mission.
Obtain feedback from on installation personnel and update models as necessary.
Perform a Monte-Carlo simulation to understand the sensitivity of the model parameters.
Incorporate an ecological simulation model in NetLogo Chapter Three: Acknowledgements : Chapter Three: Acknowledgements 74 I express my gratitude to
Hayri Önal, James Westervelt, Hal Balbach, Larry Carlile, and John Macey
The participants at the
AERE session (15H) at the Annual Meeting of the Southern Economics Association in 2008.
Session 3061 at the Agricultural and Applied Economics Association Annual Meeting in August 2009.
The program for Environmental and Resource Economics (pERE) workshop at University of Illinois.
This research was partially supported by the ERDC-CERL project No.W81EWF-7204-6330 and CREES Project No. ILLU 05-0361. Slide 75: 75 Thank You For Listening!! Three Essays on Conservation: Amenity Driven Pricing in Dynamic Reserve Design, Choice Experiment of Preferences for Grassland Restoration, and Spatial Reserve Design within Military Lands : Sahan T. M. Dissanayake
Dissertation Proposal Defense
Department of Agricultural & Consumer Economics
University of Illinois
June 17th 2010 Three Essays on Conservation: Amenity Driven Pricing in Dynamic Reserve Design, Choice Experiment of Preferences for Grassland Restoration, and Spatial Reserve Design within Military Lands Chapter Summaries – Chapter One : Chapter Summaries – Chapter One 77 Chapter Summaries – Chapter Two : Chapter Summaries – Chapter Two 78 Chapter Summaries – Chapter Three : Chapter Summaries – Chapter Three 79 Chapter One: Literature Review : Chapter One: Literature Review 80 Large literature studying price effects of conservation.
Irwin (2002) find that private conservation lands and public open space have a positive effect on property values.
Neumann et al. (2009) find that a property located 100 meters closer to the National Wildlife Refuge (NWR) than a neighboring property has a price premium of $984.00. Chapter One: Literature Review : Chapter One: Literature Review 81 Price effects in dynamic reserve design:
Increase in the price of the land parcels in the first period due to the entrance of the conservation agency.
Increase in the price of remaining land parcels of that landscape due to the reduced supply of land.
Increase in the price of land parcels adjacent to the reserves due to the amenity driven increase in demand specific to those land parcels.
(Costello and Polasky 2004, Armsworth et al. 2006 and Harpankar unpublished-2006) Chapter One: Methods : Chapter One: Methods 82 We consider three market clearing land prices
One first period market clearing prices
p1 = p0 + price increase due to period one land market effects
Two second period market clearing prices
p2 = p1 + price increase due to period two land market effects
p3 = p2 + location based amenity price effects (pa),
(only for sites that are adjacent to first period purchases)
For the simulation we assume p1 =1 and that p2 > p1.
The location based amenity price premium is specified by pa = p3 – p2
We test the model over a range of values for pa Chapter One: Methods : Chapter One: Methods 83 The Monte Carlo Simulation Chapter One: Methods : Chapter One: Methods 84 Incorporating Uncertainty
The Monte Carlo framework presented above allows uncertainty of ecological suitability to be included into the analysis.
In the first period assume the second period ecological benefit is (1-p)ek.
At the start of the second period, randomly choose p*S sites that are unavailable.
Solve the second period, the available sites ( S* (1-p) sites)) have ecological benefit ek.
We analyze the model under varying levels of uncertainty. Chapter One: Results : Chapter One: Results 85 Analysis of Objective Function Weights Chapter One: Appendix A – The Model : Chapter One: Appendix A – The Model 86 Chapter One: Appendix A – The Model : Chapter One: Appendix A – The Model 87 Why Dynamic Models : Why Dynamic Models 88 Land Price Changes
Armsworth (2006) graphically analyses the change in land prices due to conservation use: The competitive equilibrium without conservation is at (q1, p1)
Conservation group with budget B enters the market
Aggregate demand curve D~
New equilibrium at (q2, p2)
The shaded rectangle is the conservation budget B = p2qc.
Accurate depiction of reality? Chapter Two: Motivation : Chapter Two: Motivation 89 The increasing loss of grasslands in North America is a growing conservation crisis.
deforestation in the eastern United States
fragmentation and replacement of prairie vegetation with a modern agricultural landscape
large-scale deterioration of western U.S. rangelands
(Brennan and Kuvlesky, 2005) Pivot Irrigated Farming in Kansas
Area 37.2 x 38.8 km
(NASA Landcover Data) Chapter Two: Motivation : Chapter Two: Motivation 90 Distributions of the greater prairie chicken in Illinois (Anderson 1970) Greater Prairie Chicken
(IDNR) Chapter Two: Motivation : Chapter Two: Motivation 91 Grasslands have value
beyond conservation Ecosystem services from grasslands in South Africa valued at 9.7 billion rand (~ 1.4 billion $) per year The carbon storage value for British Columbia’s grasslands is estimated at $21 million per year. Ecosystem services provided by the US Refuge System valued at $26.9 billion/year Chapter Two: Motivation : Chapter Two: Motivation 92 Grasslands have value
beyond conservation Ecosystem services from grasslands in South Africa valued at 9.7 billion rand (~ 1.4 billion $) per year The carbon storage value for British Columbia’s grasslands is estimated at $21 million per year. Ecosystem services provided by the US Refuge System valued at $26.9 billion/year Chapter Two: Methods : Chapter Two: Methods 93 Why a choice experiment survey?
CV studies cannot calculate the WTP/Utility for individual attributes.
Binary choice questions are attractive
Less cognitive burden on the respondent
Only require comparison of two items at a time (unlike ranking, rating, and multinomial choice which require comparison amongst three or more items).
Respondents only need to make an ordinal judgment (no need to calculate a WTP). Chapter Two: Methods : Chapter Two: Methods 94 Experimental Design (3 attribute, 2 level example cont) Fractional factorial design that is not orthogonal Fractional factorial design that is balanced and orthogonal Chapter Two: Methods : Chapter Two: Methods 95 Empirical design
Survey designs are typically evaluated using D-efficiency
D-efficient designs require
The design achieves a 99.57% D-efficiency and can be implemented with 54 choice profiles.
We will create a block design where the 54 choice sets will be separated into blocks of 6 choice profiles, giving 9 unique surveys. Chapter Two: Methods : Chapter Two: Methods 96 The Attributes Chapter Two: Methods : Chapter Two: Methods 97 The Attributes Chapter Three : Literature Review : Chapter Three : Literature Review 98 We contribute to the reserve design literature but given that the selected areas will be within the boundaries of military installations where the primary goal is the military readiness we use the term Conservation Management Area (CMA) to refer to the selected areas.
Mathematical programming methods, have been used widely in the literature of biological conservation and reserve design since the 1980s.
Initial models were mostly heuristic and over the last fifteen years formal optimization models are being developed. Chapter Three : Literature Review : Chapter Three : Literature Review 99 In its simplest form, the problem is stated as
selecting a minimum number of habitat sites that support specified populations of a set of target species.
maximizing the number of species that can be protected by selected sites under a conservation budget constraint or area limitations.
The solution to the simples form typically results in scattered sites that are not ecologically viable.
Recent reserve design formulation incorporate various forms of spatial considerations,
connectivity, compactness, fragmentation, buffer zones Chapter Three: Multiple Landuse Model : Chapter Three: Multiple Landuse Model 100 Multiple Landuse Clustering Model