Adaptive capacity is an understudied yet is conceptually and practically important for the future as the consequences of climate change progress. Using Gallopin’s review (2006), this study created an adaptive capacity index to assess a local area’s
socioeconomic and biophysical ability to adapt, where adaptive capacity is the capacity of response and thus a subset of vulnerability in the context of global environmental change. This set of indicators was compiled into the Urbanization Adaptive Capacity Index, or UACI. Its contribution to the literature is the consideration of urbanization (primarily the transformation of vegetated land cover to build up urban land cover), as urbanization is intricately tied to climate change. The goal with the UACI is to help small locales assess their adaptive capacity and identify strengths and weaknesses. This research had the additional goals of illustrating the effect of land use change on social and environmental factors, as well as making an international comparison between two case study sites.
Using predicted land use change, we predicted changes in adaptive capacity under three different scenarios through 2 time slices, 2030 and 2050. To do this, we chose indicators correlated with LULC change and applied it to years 2000 and 2010 to find a baseline trend, each as a function of LULC change. Land use scenarios were developed based on IPCC literature.
Under all scenarios, both Tamsui and West Palm Beach lost vegetated natural land cover to development. But in Tamsui, all the UACI scores declined after the baseline year, whereas in West Palm Beach, Scenario B had an increasing score through 2030 and 2050. The results tell a general, familiar narrative-- that there are increased social and economic benefits as a place urbanizes, such as higher levels of education or income, but at some point the benefits peak and urban cons begin to overtake its benefits, particularly the environmental costs. According to our results, Tamsui has already reached that point, although this does not necessarily suggest that Tamsui is more vulnerable to climate impacts, as adaptive capacity is only a part of the equation. West Palm Beach and the rest of southern Florida are susceptible to saltwater inundation, which is a sensitivity and exposure issue, and is not linked to urbanization and thus not represented in this study. Nonetheless, it seems its adaptive capacity will decrease into the future.
For the two sites considered in this study, urbanization is shown to bring socioeconomic benefits at the cost of environmental quality. Sustainable development is a concept which aims to separate these trends and provide a way to decouple growth from environmental degradation. It is imperative that Tamsui follow a more conscientious path than a BAU approach, as even a slower growth scenario will not be sufficient to maintain a high level of adaptive capacity. Drastic measures are necessary
to adapt to the impacts resulting from climate change. Policy changes will have to be holistic and consider wellbeing in the long term in a number of different sectors, such as health, economy, transportation, energy and more.
Considering these results, we recommend that Tamsui maintain natural land cover by limiting urban sprawl and development in the mountainous areas to maintain the benefit-over-detriment balance as seen in the baseline score. While preserving the ecosystems of higher altitudes is a high priority in all of Taiwan, this model shows that total natural land cover is of great importance to adaptive capacity in the area, and thus Tamsui should be especially cautious considering its large resident and tourist population. At the same time, maintaining higher population densities can help prevent further land use change. As far as other socioeconomic strategies, fosters stronger social networks and build trust among those in the community can be beneficial for increasing adaptive capacity.
Nationwide initiatives will also be important. As Taiwan has a more centralized government and active climate change policies, national level strategies will also be necessary, especially in terms of bringing up median incomes through labor legislation or keeping inequality low through social programs and regulation.
West Palm Beach falls earlier on this urbanization curve, giving the community more leeway to keep adaptive capacity higher. But as many residents in Florida, and
more broadly across the country, do not find climate change to be a salient issue, framing adaptive capacity issues in a viable way is key. Often encouraging risk reduction and disaster preparedness more generally can be more effective than emphasizing climate change.
The maintenance of Grassy Waters Preserve in West Palm Beach has positive effects on adaptive capacity, as well as in a number of other aspects, especially since the city draws its water from the wetland. West Palm Beach is unlikely to completely open up the preserve to development, as done in our scenarios, but should take care to prevent any ecological degradation like urban encroachment, which can lead to water and air pollution. The existence of the preserve was a key factor in the outcome of the index scores.
West Palm Beach should also focus on mitigating social strain of urbanization, as the region is expecting increased demographic change, especially with regards to immigration. Some demographic groups can be at higher risk and limited access to resources, which will adversely affect indicators such as inequality, internet access, and median household income. Integrating and supporting these populations justly will be key to lowering inequality and increasing social capital.
This research presents the UACI as an introductory model that can be easily elaborated in several aspects, as future data will inevitably be available in finer scales
as well as more frequent, detailed collection. Ideally, this index would include biodiversity and other land-related indicators as data availability and access improves.
Additionally, studies on different geographic locations can reveal different findings and are key to providing a richer picture of climate adaptive capacity.
The major benefits of the UACI is that it is an easy-to-use and -understand index, ideal for small scale, quickly-urbanizing communities to see different potential trends in their adaptive capacity. This index is especially suited to assess districts in a city for comparison or other similar situations. Its importance lies in its ability to provide policy makers and planners with concrete information on which to make decisions to improve adaptive capacity.
References
Abildtrup J, Audsley E, Fekete-Farkas M, et al (2006) Socio-economic scenario development for the assessment of climate change impacts on agricultural land use: a pairwise comparison approach. Environ Sci Policy 9:101–115. doi:
10.1016/j.envsci.2005.11.002
Acosta L, Klein RJT, Reidsma P, et al (2013) A spatially explicit scenario-driven model of adaptive capacity to global change in Europe. Glob Environ Chang 23:1211–1224. doi: 10.1016/j.gloenvcha.2013.03.008
Adger, WN, Agrawala S, Mirza MMQ, et al (2007) Chapter 17: Assessment of adaptation practices, options, constraints and capacity.
Beggs JJ, Haines VA, Hurlbert J (2010) Revisiting the rural-urban contrast: personal networks in nonmetropolitan and metropolitan Setting. Rural Sociol 61:306–325.
Broda JE, Tate RP (2015) Gross Domestic Product by state.
Brooks N (2003) A conceptual framework Vulnerability , risk and adaptation : A conceptual framework.
Brooks N, Adger WN, Kelly PM (2005) The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob Environ Chang 15:151–163. doi: 10.1016/j.gloenvcha.2004.12.006
Capozzi J (2013) Palm Beach County growth begins to sprout. Palm Beach Post Capozzi J (2015) Grassy Waters Preserve: the front line in the battle over State Road
7. Palm Beach Post
Carter TR, Rovere EL (2001) Developing and applying scenarios. Clim Chang 2001 Impacts, Adapt Vulnerability – Contrib Work Gr II to Third Assess Reprot Intergov Panel Clim Chang 147–190.
Chang C (2002) The potential impact of climate change on Taiwan’ s agriculture.
Agric Econ 27:51–64. doi: 10.1111/j.1574-0862.2002.tb00104.x
Chen CY, Huang WL (2013) Land use change and landslide characteristics analysis for community-based disaster mitigation. Environ Monit Assess 185:4125–4139.
doi: 10.1007/s10661-012-2855-y
Chen D, Liu A (2006) Relation between vegetation changes, climate variables and land-use policy in Shaanxi Province , China. 223–236.
Chou T-L, Chang J-Y (2009) Urban sprawl and the politics of land use planning in urban Taiwan. Int Dev Plan Rev 30:67–92. doi: 10.3828/idpr.30.1.3
Chu H-J, Lin Y-P, Wu C-F (2010) Forecasting space-time land use change in the Paochiao Watershed of Taiwan using demand estimation and empirical
simulation approaches. Comput Sci Its Appl - Iccsa 2010, Pt 1, Proc 6016:116–
130.
Colburn L, Seara T (2011) Resilience, vulnerability, adaptive capacity, and social capital PPT. 1–14.
Conference UN (2012) Adaptive capacity. doi: 10.1007/978-94-007-4223-9
Coulston JE, Deeny P (2010) Prior exposure to major flooding increases individual preparedness in high-risk populations prior exposure to major flooding increases individual preparedness in high-risk. Prehosp Disaster Med 25:289–95. doi:
10.1017/S1049023X00008219
Cutter SL, Barnes L, Berry M, et al (2008) A place-based model for understanding community resilience to natural disasters. Glob Environ Chang 18:598–606. doi:
10.1016/j.gloenvcha.2008.07.013
Dale VH (1997) The relationship between land-use change and climate change. Ecol Appl 7:753–769.
Daramola AY, Oni Timothy O, Ogundele O, Adesanya A (2016) Adaptive capacity and coping response strategies to natural disasters: a study in Nigeria. Int J Disaster Risk Reduct. doi: 10.1016/j.ijdrr.2016.01.007
Engle NL (2011) Adaptive capacity and its assessment. Glob Environ Chang 21:647–
656. doi: 10.1016/j.gloenvcha.2011.01.019
Ensor JE, Park SE, Hoddy ET, Ratner BD (2015) A rights-based perspective on adaptive capacity. Glob Environ Chang 31:38–49. doi:
10.1016/j.gloenvcha.2014.12.005
Fanjiang Y, Kuo J, Ma S, Huang W (2010) Computational science and its applications – ICCSA 2010. 6017:257–272. doi: 10.1007/978-3-642-12165-4
Folke C (2006) Resilience: The emergence of a perspective for social-ecological systems analyses. Glob Environ Chang 16:253–267. doi:
10.1016/j.gloenvcha.2006.04.002
Fu P, Weng Q (2016) A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery.
Remote Sens Environ 175:205–214. doi: 10.1016/j.rse.2015.12.040
Gallop (2015) US views on climate change stable after extreme winter. In: Gallop.
Group T, Support S, Assessment C, et al (2007) General guidelines on the use of scenario data for climate impact. Environment 312:1–65. doi: 10.1144/SP312.4 Guan D, Li H, Inohae T, et al (2011) Modeling urban land use change by the
integration of cellular automaton and Markov model. Ecol Modell 222:3761–
3772. doi: 10.1016/j.ecolmodel.2011.09.009
Haines-Young R (2009) Land use and biodiversity relationships. Land use policy 26:178–186. doi: 10.1016/j.landusepol.2009.08.009
Hinkel J (2011) “ Indicators of vulnerability and adaptive capacity”: Towards a clarification of the science-policy interface. Glob Environ Chang 21:198–208.
doi: 10.1016/j.gloenvcha.2010.08.002
Ho SPS, Lin GCS (2004) Converting land to nonagricultural use in China’s Coastal Provinces: Evidence from Jiangsu. Mod China 30:81–112. doi:
10.1177/0097700403259131
Hogarth JR, Wójcik D (2016) An evolutionary approach to adaptive capacity
assessment: A case study of Whitehouse, Jamaica. J Rural Stud 43:248–259. doi:
10.1016/j.jrurstud.2015.12.005
Hope R, Hope KR, Edge WA (1996) Growth with uneven development : urban- rural socio-economic disparities in Botswana growth with uneven development : urban-rural socio-economic disparities in Botswana. Geoforum. doi:
10.1016/0016-7185(95)00031-3
Hsu H, Chen C (2002) Observed and projected climate change in Taiwan.
Hsu, Chou, Wu, et al (2011) Climate change in Taiwan : Scientific Report 2011 Climate change in Taiwan : Scientific Report 2011.
IPCC (2000) Summary for Policymakers: Emissions Scenarios. A special report of Working Group III of the Intergovernmental Panel on Climate Change.
IPCC (2001) Climate Change 2001. Synthesis Report. Contribution of Working Groups I, II and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland. IPCC (2001)
Intergovernmental Panel on Climate Change. http://www.ipcc.ch/index.htm IPCC (2012) Managing the Risks of Extreme Events and Disasters to Advance
Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C.B., V. Barros, T.F.
Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K.
Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, UK,and New York, NY, USA, 582 pp.IPCC (2014) Scenario
process for AR5. In: IPCC Data Distrib. Cent. http://sedac.ipcc-data.org/ddc/ar5_scenario_process/index.html. Accessed 9 Oct 2015 IPCC (2014) Climate Change 2014: Synthesis Report. Contribution of Working
Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp. IPCC (2016) Intergovernmental
Johnston M, Hesseln H (2012) Climate change adaptive capacity of the Canadian forest sector. For Policy Econ 24:29–34. doi: 10.1016/j.forpol.2012.06.001 Jones AD, Collins WD, Edmonds J, et al (2013) Greenhouse gas policy influences
climate via direct effects of land-use change. J Clim 26:3657–3670. doi:
10.1175/JCLI-D-12-00377.1
Jubeh G, Mimi Z (2012) Governance and climate vulnerability index. Water Resour Manag 26:4147–4162. doi: 10.1007/s11269-012-0137-7
KC B, Shepherd JM, Gaither CJ (2015) Climate change vulnerability assessment in Georgia. Appl Geogr 62:62–74. doi: 10.1016/j.apgeog.2015.04.007
Kelly PM, Adger WN (2000) Theory and practice in assessing vulnerability to climate change and facilitating adaptation. Clim Change 47:325–352. doi:
10.1023/A:1005627828199
Lan Y-J, Hsu T-W, Lin Y-C, Huang C-J (2013) An adaptation due to climate change in southwest Coast of Taiwan. Coast Manag 41:172–189. doi:
10.1080/08920753.2013.768514
Lee CL, Huang SL, Chan SL (2009) Synthesis and spatial dynamics of
socio-economic metabolism and land use change of Taipei Metropolitan Region. Ecol Modell 220:2940–2959. doi: 10.1016/j.ecolmodel.2009.06.021
Lee H-L (2009) The impact of climate change on global food supply and demand, food prices, and land use. Paddy Water Environ 7:321–331. doi:
10.1007/s10333-009-0181-y
Leiserowitz A, Maibach E, Roser-Renouf C, et al (2015) Climate change in the American mind: October 2015. New Haven
Li X, Li W, Middel A, et al (2016) Remote sensing of the surface urban heat island and land architecture in Phoenix, Arizona: Combined effects of land composition and configuration and cadastral-demographic-economic factors. Remote Sens Environ 174:233–243. doi: 10.1016/j.rse.2015.12.022
Liao CH, Chang CL, Su CY, Chiueh PT (2013) Correlation between land-use change and greenhouse gas emissions in urban areas. Int J Environ Sci Technol
10:1275–1286. doi: 10.1007/s13762-012-0155-2
Lim B, Spanger-siegfried E, Burton I, et al (2004) Adaptation policy frameworks for climate change : developing strategies, policies and measures.
Lin FT (2000) GIS-based information flow in a land-use zoning review process.
Landsc Urban Plan 52:21–32. doi: 10.1016/S0169-2046(00)00110-9
Lin FT, Tseng W-Y (2010) Using cellular automata model to simulate the impact of urban growth policy on environment in Danshuei Township, Taiwan. Comput Sci Its Appl – ICCSA 2010 6017:257–272. doi: 10.1007/978-3-642-12165-4 Lin YP, Verburg PH, Chang CR, et al (2009) Developing and comparing optimal and
empirical land-use models for the development of an urbanized watershed forest in Taiwan. Landsc Urban Plan 92:242–254. doi:
10.1016/j.landurbplan.2009.05.003
Lin Y-P, Chu H-J, Wu C-F, Verburg PH (2011) Predictive ability of logistic
regression, auto-logistic regression and neural network models in empirical land-use change modeling – a case study. Int J Geogr Inf Sci 25:65–87. doi:
10.1080/13658811003752332
Lin Y-P, Hong N-M, Wu P-J, et al (2007) Impacts of land use change scenarios on hydrology and land use patterns in the Wu-Tu watershed in Northern Taiwan.
Landsc Urban Plan 80:111–126. doi: 10.1016/j.landurbplan.2006.06.007
Maimaitiyiming M, Ghulam A, Tiyip T, et al (2014) Effects of green space spatial
Marshall CH, Pielke R a, Steyaert LT (2003) Wetlands: crop freezes and land-use change in Florida. Nature 426:29–30. doi: 10.1038/426029a
Maslin M (2009) Global warming: A very short introduction (Very Short Introductions).
McManus P, Shrestha KK, Yoo D (2014) Equity and climate change: local adaptation issues and responses in the City of Lake Macquarie, Australia. Urban Clim 10:1–
18. doi: 10.1016/j.uclim.2014.08.003
Metzger MJ, Rounsevell MD a, Acosta-Michlik L, et al (2006) The vulnerability of ecosystem services to land use change. Agric Ecosyst Environ 114:69–85. doi:
10.1016/j.agee.2005.11.025
Mohan M, Pathan SK, Narendrareddy K, et al (2011) Dynamics of urbanization and its impact on land-use / Land-Cover : A Case Study of Megacity Delhi.
2011:1274–1283. doi: 10.4236/jep.2011.29147
Monterroso A, Conde C, Gay C, et al (2014) Two methods to assess vulnerability to climate change in the Mexican agricultural sector. Mitig Adapt Strateg Glob Chang 19:445–461. doi: 10.1007/s11027-012-9442-y
Nations U (2014) World Urbanization Prospects.
Nhuan MT, Tue NT, Hue NTH, et al (2016) An indicator-based approach to quantifying the adaptive capacity of urban households: The case of Da Nang city, Central Vietnam. Urban Clim 15:60–69. doi: 10.1016/j.uclim.2016.01.002 Normander B, Levin G, Auvinen AP, et al (2012) Indicator framework for measuring
quantity and quality of biodiversity - Exemplified in the Nordic countries. Ecol Indic 13:104–116. doi: 10.1016/j.ecolind.2011.05.017
OECD (2011) Indicator A2 - Secondary Education. Organisation for Economic Co-operation and Development.
Okamoto K, Sharifi A, Chiba Y (2014) The impact of urbanization on land use and the Changing Role of Forests in Vientiane. 29–39. doi: 10.1007/978-4-431-54956-7
Oreskes N, Conway E (2010) Merchants of doubt: How a handful of scientists
obscured the truth on issues from tobacco smoke to global warming. Bloomsbury Publishing, New York
Panda A, Sharma U, Ninan KN, Patt A (2013) Adaptive capacity contributing to improved agricultural productivity at the household level: Empirical findings highlighting the importance of crop insurance. Glob Environ Chang 23:782–790.
doi: 10.1016/j.gloenvcha.2013.03.002
Pandey R, Bardsley DK (2015) Social-ecological vulnerability to climate change in the Nepali Himalaya. Appl Geogr 64:74–86. doi: 10.1016/j.apgeog.2015.09.008 Pettit CJ (2005) Use of a collaborative GIS-based planning support system to assist in
formulating a sustainable-development scenario for Hervey Bay, Australia.
Environ Planning, B Plan Des 32:523–546.
Pielke RA, Pitman A, Niyogi D, et al (2011) Land use / land cover changes and climate : modeling analysis and observational evidence. doi: 10.1002/wcc.144 Posey J (2009) The determinants of vulnerability and adaptive capacity at the
municipal level: Evidence from floodplain management programs in the United States. Glob Environ Chang 19:482–493. doi: 10.1016/j.gloenvcha.2009.06.003 Pradhan BK, Roy PK, Saluja MR, Venkatrum S (2000) Rural-urban disparities:
income distribution, expenditure pattern and social sector.
Pyke CR, Andelman SJ (2007) Land use and land cover tools for climate adaptation.
Clim Change 80:239–251. doi: 10.1007/s10584-006-9110-x
Quiroga S, Suarez C, Solis JD (2015) Exploring coffee farmers’ awareness about climate change and water needs: Smallholders' perceptions of adaptive capacity.
Environ Sci Policy 45:53–66. doi: 10.1016/j.envsci.2014.09.007
Rounsevell MD a, Reginster I, Araújo MB, et al (2006) A coherent set of future land
Salik KM, Jahangir S, Ul W, et al (2015) Climate change vulnerability and adaptation options for the coastal communities of Pakistan. Ocean Coast Manag 112:61–73.
doi: 10.1016/j.ocecoaman.2015.05.006
Sietchiping R (2006) Applying an index of adaptive capacity to climate change in north-western Victoria, Australia. Appl GIS 2:16.1–16.28. doi:
10.2104/ag060016
Simões AF, Kligerman DC, Rovere EL La, et al (2010) Enhancing adaptive capacity to climate change: The case of smallholder farmers in the Brazilian semi-arid region. Environ Sci Policy 13:801–808. doi: 10.1016/j.envsci.2010.08.005 Smit B, Burton I, Klein RJT, Wandel J (2000) An Anatomy of Adaptation to Climate
Change and Variability. Clim Chang 45:223–251.
Smit B et al (2001) Adaptation to climate change in the context of sustainable development and equity.
Su Y (2011) The international legal concerns on climate change regime : Taiwan’s Perspective. J East Asia Int Law 63–80.
The World Bank (2015) Internet Users (per 100 people).
http://data.worldbank.org/indicator/IT.NET.USER.P2.
Thulstrup AW (2015) Livelihood resilience and adaptive capacity: tracing changes in household access to capital in central Vietnam. World Dev 74:352–362. doi:
10.1016/j.worlddev.2015.05.019
UN (2014) Contribution to the 2014 United Nations Economic and Social Council ( ECOSOC ) Integration Segment.
UN Habitat (2011) State of the world’s cities 2010/2011. United Nations.
USDA (2015) Rural education levels improve, still lag urban areas.
http://www.ers.usda.gov/data-products/chart-gallery/detail.aspx?chartId=55622.
Accessed 15 Jan 2016
Vincent K (2007) Uncertainty in adaptive capacity and the importance of scale. Glob Environ Chang 17:12–24. doi: 10.1016/j.gloenvcha.2006.11.009
Walker R, Solecki W, Walker R, Solecki W (2016) Theorizing cover and land-use change: the case of the Florida Everglades and its degradation. Ann Assoc Am Geogr. doi: 10.1111/j.1467-8306.2004.09402010.x
Xenarios S, Nemes A, Sarker GW, Sekhar NU (2016) Assessing vulnerability to climate change: Are communities in flood-prone areas in Bangladesh more vulnerable than those in drought-prone areas? Water Resour Rural Dev 7:1–19.
doi: 10.1016/j.wrr.2015.11.001
Yohe G, Tol RSJ (2002) Indicators for social and economic coping capacity F moving toward a working definition of adaptive capacity. Glob Environ Chang 12:25–40.
Zhou W, Ji S, Chen TH, et al (2014) The 2011 heat wave in Greater Houston: effects of land use on temperature. Environ Res 135:81–87. doi:
10.1016/j.envres.2014.08.025
Ziersch AM, Baum F, Kavanagh AM, Bentley RJ (2009) Social capital and health in rural and urban communities in South Australia. doi:
10.1111/j.1753-6405.2009.00332.x