Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs.

Lisa A Wainger,Anna M Mcmurray,Dong Liang,Cedric Magen,Al F Cofrancesco,Nathan E Harms,Genevieve M Nesslage

doi:10.7717/peerj.4824

Abstract

Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth (Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would be 76% higher without the substantial growth rate suppression (84% reduction) that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975–2013), generated a benefit-cost ratio of about 34:1 derived from the relatively modest costs of $124 million ($2013) compared to the $4.2 billion ($2013) in benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities over the 38-year analysis period. This work adds to the literature by: (1) providing evidence of the effectiveness of water hyacinth biological control; (2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive species control; and (3) incorporating activity substitution into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control.

Highlights

How to cite this article Wainger et al (2018), Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs
Our cost benefit analysis revealed that water hyacinth control, largely the result of biological control, has generated benefits in Louisiana well in excess of research, development, and implementation costs
Using the four ecosystem services with the best data, we estimated a benefit cost (B/C) ratio of 34:1, due to all forms of control. This high ratio for aquatic plant control is consistent with other literature that safe and effective biological control agents generate net benefits (Lovell, Stone & Fernandez, 2006) and can dramatically lower management costs of control (Hinz et al, 2014)

Summary

Introduction

How to cite this article Wainger et al (2018), Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs. Robust demonstration of invasive species management program benefits may be crucial to maintaining programs with tight budgets over the long term, if programs are successful at reducing harms, thereby reducing the apparent urgency of action Such analyses are not possible if agencies do not collect the appropriate data and information. For economic evaluations to enable efficient allocation of scarce invasive control resources, values (or indicators of value) must measure outcomes for which people would be willing to pay or otherwise trade off other goods and services This basic concept, which is fundamental to economic theory, is often obfuscated by studies that quantify benefits of invasive species control in monetary terms that are not measuring economic benefits. Sophisticated models are time-consuming or impossible to build for many datapoor case studies and their use is far from routine for evaluating management options

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