| Literature DB >> 25333619 |
Julian D Olden1, Mariana Tamayo2.
Abstract
Economic evaluations of invasive species are essential for providing comprehensive assessments of the benefits and costs of publicly-funded management activities, yet many previous investigations have focused narrowly on expenditures to control spread and infestation. We use hedonic modeling to evaluate the economic effects of Eurasian milfoil (Myriophyllum spicatum) invasions on lakefront property values of single-family homes in an urban-suburban landscape. Milfoil often forms dense canopies at the water surface, diminishing the value of ecosystem services (e.g., recreation, fishing) and necessitating expensive control and management efforts. We compare 1,258 lakeshore property sale transactions (1995-2006) in 17 lakes with milfoil and 24 un-invaded lakes in King County, Washington (USA). After accounting for structural (e.g., house size), locational (e.g., boat launch), and environmental characteristics (e.g., water clarity) of lakes, we found that milfoil has a significant negative effect on property sales price ($94,385 USD lower price), corresponding to a 19% decline in mean property values. The aggregate cost of milfoil invading one additional lake in the study area is, on average, $377,542 USD per year. Our study illustrates that invasive aquatic plants can significantly impact property values (and associated losses in property taxes that reduce local government revenue), justifying the need for management strategies that prevent and control invasions. We recommend coordinated efforts across Lake Management Districts to focus institutional support, funding, and outreach to prevent the introduction and spread of milfoil. This effort will limit opportunities for re-introduction from neighboring lakes and incentivize private landowners and natural resource agencies to commit time and funding to invasive species management.Entities:
Mesh:
Year: 2014 PMID: 25333619 PMCID: PMC4198248 DOI: 10.1371/journal.pone.0110458
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Location of milfoil presences (red filled circle) and absences (white empty circles) in lakes of Washington, USA, including King County (bottom right) containing 17 invaded lakes (filled squares) and 24 uninvaded lakes (empty squares).
The city of Seattle, Washington (2010 population size of 608,660) is indicated as *.
Structural, locational, and environmental independent variables used in the hedonic analysis of property sales price (*).
| Variable | Description | Mean | S.E. |
| Sales price* | Selling price of the property (land + house; 2006 USD) | 502312.8 | 23942.4 |
|
| |||
| Lot size | Size of a parcel (m2) | 2394.5 | 216.2 |
| Frontage | Shoreline frontage of a property (m2) | 22.0 | 1.1 |
| House size | Total living area (m2) | 204.8 | 6.6 |
| House age | Age of a house (years) | 39.5 | 1.6 |
|
| |||
| Boat launch | Presence of a public boat launch | 0.6 | 0.1 |
| Fish stocking | Presence of fish stocking for recreational angling | 0.7 | 0.1 |
| Parcel density | Number of parcels per km2 | 512.1 | 35.6 |
|
| |||
| Milfoil presence | Presence of Eurasian milfoil | 0.4 | 0.1 |
| Lake area | Surface area of a lake adjacent to the property (km2) | 0.2 | 0.03 |
| Temperature | Mean surface water temperature during the milfoilsummer growing season (°C) | 19.8 | 0.3 |
| Water clarity | Mean Secchi depth of the lake during the milfoilgrowing season (m) | 3.4 | 0.2 |
Hedonic analysis results for the two-stage least squares regression model predicting property price as a function of key independent variables describing structure, location, and the environment (see Table 1).
| Model 1 | Model 2 | Model 3 | |||||||
| Variable | Coefficient | Sig. | S.E. | Coefficient | Sig. | S.E. | Coefficient | Sig. | S.E. |
| Constant | −63891.9 | 97303.1 | −29052.8 | 117533.5 | −95790.7 | 149910.1 | |||
| Milfoil presence | −94385.4 | ** | 46712.9 | −94670.0 | * | 49174.7 | −92558.0 | * | 48255.6 |
| House size | 2608.1 | *** | 344.2 | 2474.0 | *** | 703.9 | 2681.6 | *** | 726.0 |
| Lot size | −1.2 | 13.2 | 3.1 | 12.9 | |||||
| Parcel density | 102.8 | 70.3 | 115.4 | 78.6 | |||||
| Lake area | 209407.8 | ** | 81848.0 | 154409.5 | * | 74073.6 | 215595.0 | ** | 84521.5 |
| Water clarity | −7430.3 | 11160.2 | −6962.7 | 12820.2 | −6954.9 | 12600.7 | |||
| AICc | 23.931 | 23.986 | 23.998 | ||||||
| Relative likelihood | 1.000 | 0.969 | 0.963 | ||||||
See text for discussion of the endogenous variable (milfoil presence) and instrumental variables. Reported are the top three candidate models according to Akaike’s Information Criterion for small samples (AICc) with their associated parameter coefficients and standard errors. The relative likelihood that the model is the best model given the data is denoted.
Significant levels: *P<0.10, **P<0.05, ***P<0.01.