Abstract
While cost estimation is a very positive tool for spatial conservation prioritisation, there are few examples where costs (in monetary terms) are applied. We present a repeatable method to estimate and map field values in monetary terms using common correlative models. We modelled, with a resolution of 1 km2, the information obtained by several real estate’s agencies with a set of eleven environmental, climatic, and anthropogenic variables. Land cover was the main influencing factor, but further variables were affecting bids on field sales according to the socio-economic specificity of each administrative province. The estimated values were related to endemic plant species richness, their conservation status and altitudinal ranges. Richest areas in endemics have lower values given current market conditions and, within these endemic rich areas, values near the coast were generally higher than the rest of endemic-rich territories. Despite their limits, our method offers an alternative perspective on the challenges of simplifying the extrapolation of useful information for planning and disseminating the conservation of many ecosystem services providers.
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References
Andersen, R., C. Farrell, M. Graf, F. Muller, E. Calvar, P. Frankard, S. Caporn, and P. Anderson. 2017. An overview of the progress and challenges of peatland restoration in Western Europe. Restoration Ecology 25: 271–282. https://doi.org/10.1111/rec.12415.
Araújo, M.B. 2004. Matching species with reserves–uncertainties from using data at different resolutions. Biological Conservation 118: 533–538. https://doi.org/10.1016/j.biocon.2003.10.006.
Armsworth, P.R., and J.N. Sanchirico. 2008. The effectiveness of buying easements as a conservation strategy. Conservation Letters 1: 182–189. https://doi.org/10.1111/j.1755-263X.2008.00028.x.
Ball, I.R., H.P. Possingham, and M. Watts. 2009. Marxan and relatives: software for spatial conservation prioritization. In Spatial conservation prioritisation: Quantitative methods and computational tools, ed. A. Moilanen, K. Wilson, and H. Possingham, 185–195. Oxford: Oxford University Press.
Balmford, A., K.J. Gaston, S. Blyth, A. James, and V. Kapos. 2003. Global variation in terrestrial conservation costs, conservation benefits, and unmet conservation needs. Proceedings of the National Academy of Sciences of United States of America 100: 1046–1050. https://doi.org/10.1073/pnas.0236945100.
Barbosa, A.M., J.A. Brown, A. Jimenez-Valverde, and R. Real. 2014. ModEvA: Model Evaluation and Analysis. R Package, version 1.1. http://modeva.r-forge.r-project.org/modEvA-tutorial.html. Retrieved 1 March 2017.
Bastian, C.T., D.M. McLeod, M.J. Germino, W.A. Reiners, and B.J. Blasko. 2002. Environmental amenities and agricultural land values: A hedonic model using geographic information systems data. Ecological Economics 40: 337–349. https://doi.org/10.1016/S0921-8009(01)00278-6.
Bosso, L., M. Febbraro, G. Cristinzio, A. Zoina, and D. Russo. 2016. Shedding light on the effects of climate change on the potential distribution of Xylella fastidiosa. Biological Invasions 18: 1759–1768. https://doi.org/10.1007/s10530-016-1118-1.
Brooks, T.M., R.A. Mittermeier, G.A.B. da Fonseca, J. Gerlach, M. Hoffmann, J.F. Lamoreux, C.G. Mittermeier, J.D. Pilgrim, et al. 2006. Global biodiversity conservation priorities. Science 313: 58–61. https://doi.org/10.1126/science.1127609.
Dalerum, F. 2014. Identifying the role of conservation biology for solving the environmental crisis. Ambio 43: 839–846. https://doi.org/10.1007/s13280-014-0546-3.
Degteva, S.V., V.I. Ponomarev, S.W. Eisenman, and V. Dushenkov. 2015. Striking the balance: Challenges and perspectives for the protected areas network in northeastern European Russia. Ambio 44: 473–490. https://doi.org/10.1007/s13280-015-0636-x.
Diniz-Filho, J.A.F., L.M. Bini, and B.A. Hawkins. 2003. Spatial autocorrelation and red herrings in geographical ecology. Global Ecology and Biogeography 12: 53–64. https://doi.org/10.1046/j.1466-822X.2003.00322.x.
Disselhoff, T. 2015. Alternative ways to support private land conservation. Natura 2000, LIFE Programme, Report E.3-PO/07.020300/2015/ENV, Berlin, Germany.
Feng, X., M.C. Castro, K. McBee, and M. Papeş. 2017. Hiding in a cool climatic niche in the tropics? An assessment of the ecological biogeography of hairy long-nosed armadillos (Dasypus pilosus). Tropical Conservation Science 10: 1–13. https://doi.org/10.1177/1940082917697249.
Fois, M., G. Fenu, and G. Bacchetta. 2016. Global analyses underrate part of the story: Finding applicable results for the conservation planning of small Sardinian islets’ flora. Biodiversity and Conservation 25: 1091–1106. https://doi.org/10.1007/s10531-016-1110-1.
Fois, M., G. Fenu, E.M. Cañadas, and G. Bacchetta. 2017. Disentangling the influence of environmental and anthropogenic factors on the distribution of endemic vascular plants in Sardinia. PLoS ONE 12: e0182539. https://doi.org/10.1371/journal.pone.0182539.
Fois, M., G. Bacchetta, A. Cuena-Lombraña, D. Cogoni, M.S. Pinna, E. Sulis, and G. Fenu. 2018a. Using extinctions in species distribution models to evaluate and predict threats: a contribution to plant conservation planning on the island of Sardinia. Environmental Conservation 45: 11–19. https://doi.org/10.1017/S0376892917000108.
Fois, M., G. Fenu, and G. Bacchetta. 2018b. Identifying and assessing the efficiency of different networks of a fine-scale hierarchy of biodiversity hotspots. Plant Ecology & Diversity. https://doi.org/10.1080/17550874.2018.1474281.
Gravel, N., A. Michelangeli, and A. Trannoy. 2006. Measuring the social value of local public goods: an empirical analysis within Paris metropolitan area. Applied Economics 38: 1945–1961. https://doi.org/10.1080/00036840500427213.
Guisan, A., and N.E. Zimmermann. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 38: 147–186. https://doi.org/10.1016/S0304-3800(00)00354-9.
Haase, D., N. Larondelle, E. Andersson, M. Artmann, S. Borgström, J. Breuste, E. Gomez-Baggethun, Å. Gren, et al. 2014. A quantitative review of urban ecosystem service assessments: Concepts, models, and implementation. Ambio 43: 413–433. https://doi.org/10.1007/s13280-014-0504-0.
Hijmans, R., and J. van Etten. 2014. Raster: Geographic data analysis and modeling. R package version 2.2-31. https://cran.r-project.org/web/packages/raster/index.html.
Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones, and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965–1978. https://doi.org/10.1002/joc.1276.
Hwang, M., and J. Quigley. 2004. Selectivity, quality adjustment and mean reversion in the measurement of house values. Journal Real Estate Finance and Economics 28: 191–214. https://doi.org/10.1023/B:REAL.0000011152.40485.12.
Ioppolo, G., G. Saija, and R. Salomone. 2013. From coastal management to environmental management: The sustainable eco-tourism program for the mid-western coast of Sardinia (Italy). Land Use Policy 31: 460–471. https://doi.org/10.1016/j.landusepol.2012.08.010.
ISTAT. 2014. Italy in numbers (In Italian). Roma: Istituto Nazionale di Statistica.
Köberl, J., F. Prettenthaler, and D.N. Bird. 2016. Modelling climate change impacts on tourism demand: A comparative study from Sardinia (Italy) and Cap Bon (Tunisia). Science of the Total Environment 543: 1039–1053. https://doi.org/10.1016/j.scitotenv.2015.03.099.
Kostov, P. 2009. Spatial dependence in agricultural land prices: Does it exist? Agricultural Economics 40: 347–353. https://doi.org/10.1111/j.1574-0862.2009.00375.x.
Lindborg, T., L. Brydsten, G. Sohlenius, M. Strömgren, E. Andersson, and A. Löfgren. 2013. Landscape development during a glacial cycle: Modeling ecosystems from the past into the future. Ambio 42: 402–413. https://doi.org/10.1007/s13280-013-0407-5.
Ma, S., and S.M. Swinton. 2011. Valuation of ecosystem services from rural landscapes using agricultural land prices. Ecological Economics 70: 1649–1659. https://doi.org/10.1016/j.ecolecon.2011.04.004.
Mallawaarachchi, T., M.D. Morrison, and R.K. Blamey. 2006. Choice modelling to determine the significance of environmental amenity and production alternatives in the community value of peri-urban land: Sunshine Coast, Australia. Land Use Policy 23: 323–332. https://doi.org/10.1016/j.landusepol.2004.11.004.
Mendoza-Fernández, A.J., F.J. Pérez-García, F. Martínez-Hernández, E. Salmerón-Sánchez, J.M. Medina-Cazorla, J.A. Garrido-Becerra, M.I. Martínez-Nieto, M.E. Merlo, and J.F. Mota. 2015. Areas of endemism and threatened flora in a Mediterranean hotspot: Southern Spain. Journal for Nature Conservation 23: 35–44. https://doi.org/10.1016/j.jnc.2014.08.001.
Miska, L., and H. Jan. 2005. Evaluation of current statistical approaches for predictive geomorphological mapping. Geomorphology 67: 299–315. https://doi.org/10.1016/j.geomorph.2004.10.006.
Mogush, P., K.J. Krizek, and D. Levinson. 2016. The value of bicycle trail access in home purchases. In Accessibility, equity and efficiency. Challenges for transport and public services, ed. K.T. Geurs, R. Patuelli, and T. Ponce Dentino, 193–209. Cheltenham: Edward Elgar.
Moilanen, A., and H. Kujala. 2008. Spatial conservation planning framework and software v2.0: User manual. Helsinki: Department of Biological and Environment Sciences, University of Helsinki.
Naidoo, R., and T.H. Ricketts. 2006. Mapping the economic costs and benefits of conservation. PLoS Biology 4: e360. https://doi.org/10.1371/journal.pbio.0040360.
Naimi, B., N.A. Hamm, T.A. Groen, A.K. Skidmore, and A.G. Toxopeus. 2014. Where is positional uncertainty a problem for species distribution modelling? Ecography 37: 191–203. https://doi.org/10.1111/j.1600-0587.2013.00205.x.
Newburn, D., S. Reed, P. Berck, and A. Merenlender. 2005. Economics and land-use change in prioritizing private land conservation. Conservation Biology 19: 1411–1420. https://doi.org/10.1111/j.1523-1739.2005.00199.x.
Pungetti, G., A. Marini, and I.N. Vogiatzakis. 2008. Sardinia. In Mediterranean Island Landscapes, ed. I.N. Vogiatzakis, G. Pungetti, and A.M. Mannion, 143–169. Netherlands: Springer.
R Development Core Team. 2010. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
Rangel, T.F., J.A.F. Diniz-Filho, and L.M. Bini. 2010. SAM: a comprehensive application for spatial analysis in macroecology. Ecography 33: 46–50. https://doi.org/10.1111/j.1600-0587.2009.06299.x.
Rosen, S. 1974. Hedonic prices and implicit markets: product differentiation in pure competition. Journal of Political Economy 82: 34–55. http://www.jstor.org/stable/1830899.
Sanderson, E.W., M. Jaiteh, M.A. Levy, K.H. Redford, A.V. Wannebo, and G. Woolmer. 2002. The Human Footprint and the Last of the Wild: The human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. BioScience 52: 891–904. https://doi.org/10.1641/0006-3568(2002)052[0891:THFATL]2.0.CO;2.
Segurado, P., M.B. Araujo, and W.E. Kunin. 2006. Consequences of spatial autocorrelation for niche-based models. Journal of Applied Ecology 43: 433–444. https://doi.org/10.1111/j.1365-2664.2006.01162.x.
Shaw, W.D., and M. Wlodarz. 2013. Ecosystems, ecological restoration, and economics: Does habitat or resource equivalency analysis mean other economic valuation methods are not needed? Ambio 42: 628–643. https://doi.org/10.1007/s13280-012-0351-9.
Sutton, N.J., S. Cho, and P.R. Armsworth. 2016. A reliance on agricultural land values in conservation planning alters the spatial distribution of priorities and overestimates the acquisition costs of protected areas. Biological Conservation 194: 2–10. https://doi.org/10.1016/j.biocon.2015.11.021.
Troy, A., and J.M. Grove. 2008. Property values, parks, and crime: A hedonic analysis in Baltimore, MD. Landscape and Urban Planning 87: 233–245. https://doi.org/10.1016/j.landurbplan.2008.06.005.
Turnhout, E., C. Waterton, K. Neves, and M. Buizer. 2013. Rethinking biodiversity: from goods and services to “living with”. Conservation Letters 6: 154–161.
Tyrväinen, L. 1997. The amenity value of the urban forest: An application of the hedonic pricing method. Landscape and Urban Planning 37: 211–222. https://doi.org/10.1016/S0169-2046(97)80005-9.
Underwood, E.C., K.R. Klausmeyer, S.A. Morrison, M. Bode, and M.R. Shaw. 2009. Evaluating conservation spending for biodiversity return: A retrospective analysis in California. Conservation Letters 2: 130–137. https://doi.org/10.1111/j.1755-263X.2008.00018.x.
Walsh, C., and R. Nally. 2008. Hier.Part: Hierarchical Partitioning. R Package Version 1.0-3. https://cran.r-project.org/web/packages/hier.part/index.html. Retrieved 20 February 2016.
Wildlife Conservation Society (WCS), Center for International Earth Science Information Network (CIESIN)/Columbia University. 2005. Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Influence Index (HII) Dataset (Geographic), Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4BP00QC. Retrieved 1 February 2015.
Yang, Z., M.T. Sykes, E. Hanna, and T.V. Callaghan. 2012. Linking fine-scale sub-arctic vegetation distribution in complex topography with surface-air-temperature modelled at 50-m resolution. Ambio 41: 292–302. https://doi.org/10.1007/s13280-012-0307-0.
Zuur, A., E.N. Ieno, N.J. Walker, A.A. Saveliev, and G.M. Smith. 2009. Mixed effects models and extensions in ecology with R. New York: Springer.
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We would like to thank all people who provided field and unpublished data. We are also grateful to the Editor and the anonymous reviewers for their critical comments and suggestions.
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Fois, M., Fenu, G. & Bacchetta, G. Estimating land market values from real estate offers: A replicable method in support of biodiversity conservation strategies. Ambio 48, 313–323 (2019). https://doi.org/10.1007/s13280-018-1074-3
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DOI: https://doi.org/10.1007/s13280-018-1074-3