Factors Influencing Farmers’ Participation in Contractual Biodiversity Conservation: A Choice Experiment with Northern Australian Pastoralists

Private landholders’ contributions to biodiversity conservation are critical in landscapes with insufficient formal conservation reserves, as is the case in Australia's tropical savannas. This study reports results from a discrete choice experiment conducted with pastoralists and graziers across northern Australia. The experiment was designed to explore the willingness of pastoralists and graziers to sign up to voluntary biodiversity conservation contracts. Understanding preferences for contractual attributes and preference heterogeneity were additional objectives. Such knowledge can increase effectiveness and efficiency of conservation programs by informing contract design, negotiation and administration. Random parameter logit modelling showed that of contract attributes, conservation requirement, stewardship payment, contract duration and flexibility in contract conditions significantly influenced choices. Land productivity was a significant factor as were attitudes. There was significant heterogeneity of preferences for all contract attributes. Models were run for best–worst scaling responses and the first preferences subset, with the latter model deemed superior. Latent class modelling distinguished four classes of decision‐makers and illustrated different decision heuristics. Conservation investment strategies, which offer farmers contract options that meet biodiversity requirements while accommodating heterogeneous attribute preferences, are likely to lead to increased participation rates. Complementary suasion efforts are also required which espouse the benefits that pastoralists derive from biodiversity and participation in voluntary conservation contracts.

[1]  C. Dickman,et al.  Mammals of Australia's Tropical Savannas: A Conceptual Model of Assemblage Structure and Regulatory Factors in the Kimberley Region , 2014, PloS one.

[2]  M. Wedel,et al.  Designing Conjoint Choice Experiments Using Managers' Prior Beliefs , 2001 .

[3]  J. Fitzsimons,et al.  The role of multi-tenure reserve networks in improving reserve design and connectivity , 2008 .

[4]  John Rolfe,et al.  Diversification Choices in Agriculture: A Choice Modelling Case Study of Sugarcane Growers , 2005 .

[5]  J. Woinarski The illusion of nature: perception and the reality of natural landscapes, as illustrated by vertebrate fauna in the Northern Territory, Australia , 2014 .

[6]  Suzanne Elizabeth Vedel,et al.  Using Choice Experiments to Investigate the Policy Relevance of Heterogeneity in Farmer Agri-Environmental Contract Preferences , 2012 .

[7]  Peter Burge,et al.  Best-worst scaling vs. discrete choice experiments: an empirical comparison using social care data. , 2011, Social science & medicine.

[8]  Emily Lancsar,et al.  Best worst discrete choice experiments in health: methods and an application. , 2013, Social science & medicine.

[9]  Stephen T. Garnett,et al.  Beyond cattle: potential futures of the pastoral industry in the Northern Territory , 2011 .

[10]  Uwe Latacz-Lohmann,et al.  Assessing farmers’ willingness to accept ‘greening’: insights from a discrete choice experiment in Germany , 2014 .

[11]  A. Ash,et al.  Responses of vertebrates to pastoralism, military land use and landscape position in an Australian tropical savanna , 2002 .

[12]  John M. Rose,et al.  Sample size requirements for stated choice experiments , 2013 .

[13]  Petr Mariel,et al.  Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment , 2013 .

[14]  Chris Cocklin,et al.  Ecosystem services from tropical savannas: economic opportunities through payments for environmental services , 2009 .

[15]  M. Jaeck,et al.  Farmers’ Preferences for Production Practices: A Choice Experiment Study in the Rhone River Delta , 2014 .

[16]  Kerrie A. Wilson,et al.  Farmers' willingness to provide ecosystem services and effects of their spatial distribution , 2013 .

[17]  John M. Rose,et al.  Efficient stated choice experiments for estimating nested logit models , 2009 .

[18]  K. Belcher,et al.  An Economic Analysis of Landowners’ Willingness to Adopt Wetland and Riparian Conservation Management , 2011 .

[19]  Terry N. Flynn,et al.  Best Worst Scaling: Theory and Practice , 2015 .

[20]  James Wagner,et al.  A Comparison of Alternative Indicators for the Risk of Nonresponse Bias. , 2012, Public opinion quarterly.

[21]  K. Train Halton Sequences for Mixed Logit , 2000 .

[22]  H. Nix,et al.  The nature of Northern Australia : natural values, ecological processes and future prospects , 2007 .

[23]  D. Marsh Water resource management in New Zealand: jobs or algal blooms? , 2012, Journal of environmental management.

[24]  Mette Termansen,et al.  Evaluating farmers’ likely participation in a payment programme for water quality protection in the UK uplands , 2013, Regional Environmental Change.

[25]  Nathan P. Hendricks,et al.  The role of contract attributes in purchasing environmental services from landowners , 2012 .

[26]  John Rolfe,et al.  Assessing the Trade‐Offs of Increased Mining Activity in the Surat Basin, Queensland: Preferences of Brisbane Residents Using Nonmarket Valuation Techniques , 2014 .

[27]  Michiel C.J. Bliemer,et al.  Design considerations of a choice experiment to estimate likely participation by north Australian pastoralists in contractual biodiversity conservation , 2014 .

[28]  Eric Ruto,et al.  What Do Farmers Want From Agri‐Environmental Scheme Design? A Choice Experiment Approach , 2010 .

[29]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[30]  R. Greiner,et al.  More than money for conservation: Exploring social co-benefits from PES schemes , 2013 .

[31]  I. Krinsky,et al.  On Approximating the Statistical Properties of Elasticities , 1986 .

[32]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[33]  B. Swallow,et al.  Designing a payments for ecosystem services (PES) program to reduce deforestation in Tanzania: : An assessment of payment approaches , 2013 .

[34]  David Hoyos,et al.  The state of the art of environmental valuation with discrete choice experiments , 2010 .

[35]  John M. Rose,et al.  Applied Choice Analysis: A Primer , 2005 .

[36]  G. Bortolussi,et al.  The northern Australian beef industry, a snapshot. 1. Regional enterprise activity and structure , 2005 .

[37]  David A. Hensher,et al.  Behavioural responses to vehicle emissions charging , 2009 .

[38]  G. Garrod,et al.  Investigating farmers' preferences for the design of agri-environment schemes: a choice experiment approach , 2008 .

[39]  N. Hanley,et al.  Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture , 2009 .

[40]  Stefan Hajkowicz,et al.  The evolution of Australia's natural resource management programs: Towards improved targeting and evaluation of investments , 2009 .

[41]  John M. Rose,et al.  Experimental design influences on stated choice outputs: An empirical study in air travel choice , 2009 .

[42]  Vanessa M. Adams,et al.  Estimating Landholders’ Probability of Participating in a Stewardship Program, and the Implications for Spatial Conservation Priorities , 2014, PloS one.

[43]  J. McIvor,et al.  The northern Australian beef industry, a snapshot. 2. Breeding herd performance and management , 2005 .

[44]  Romy Greiner,et al.  Motivations, risk perceptions and adoption of conservation practices by farmers , 2009 .

[45]  J. Louviere,et al.  A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling , 2008 .

[46]  T. Peters,et al.  Best--worst scaling: What it can do for health care research and how to do it. , 2007, Journal of health economics.

[47]  B. Muthén,et al.  Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study , 2007 .

[48]  John M. Rose,et al.  Confidence intervals of willingness-to-pay for random coefficient logit models , 2013 .

[49]  J. Rolfe,et al.  Valuing Options for Reserve Water in the Fitzroy Basin , 2005 .

[50]  Anders Branth Pedersen,et al.  Determinants of farmers’ willingness to participate in subsidy schemes for pesticide-free buffer zones—A choice experiment study , 2011 .