urban surface occupancy total
Biophysical Socioeconomic Total
with high growth, such has high GDP and income. But, in the final predicted time slice, 2050, Scenario A’s score decreases from its 2030 peak down to 77.2. Scenario BAU
also declines in 2050.
Despite its lower score in 2030 relative to the other scenarios, Scenario B has the highest adaptive capacity score in the end. Through 2010, 2030, and 2050, the scores for B are continuously increasing, unlike the other scenarios. The UACI scores for Scenarios A and BAU increase more quickly, peak at 2030, and start to decrease in 2050. This is due to the relatively smaller benefit of economic good of urbanizing after 2030 due to several indicators reaching maximum, while suffering increasing damages from falling environmental and social indicator scores, such as surface water runoff and inequality. Internet access is one measure of infrastructure that is more or less ubiquitous in urban areas, and by the time of the first predicted time slice all of West Palm Beach would be firmly urban “enough” to achieve high internet access in all scenarios.
Scenario A - high growth Indicator Value Score Scenario BAU - med growth Indicator Value Score Scenario B - low growth Indicator Value Score
Scenario A
Figure 25: Index scores of each scenario at each case study site over time
4.3 Discussion
The results show that Tamsui starts off with a slightly higher adaptive capacity, but West Palm Beach ends up with higher scores regardless of scenario or time slice.
However, there are several uncertainties to consider with an index measuring such a wide range of items, and human systems are complex, non-linear, and difficult to measure and predict. For example, social capital and networks are particularly difficult to measure. The source used here, World Values Survey has measured trust at 30% in Taiwan, yet another domestic source measured at 54% using the same question (Chang 2009). This huge margin of difference is troubling when it could make 2.4 points difference in the assessment, and thus ±5% overall for the total score from 2010 for this
indicator alone. Temperature differences are difficult to measure and thus extrapolate as well. In considering climate is a long term concept, a baseline of 10 years may be too short to extrapolate on, and weather conditions have many factors which may or may not cover urbanization effects. One other large uncertainty is the indicator of government plans. The quality and efficacy of government institutions and disaster planning deserves a research project of its own including both quantitative and qualitative investigation but here is simplified to a binary of existent or nonexistent.
The focus of this research was not to evaluate government efficacy; however, since up to ±10% uncertainty in this indicator can vastly affect the adaptive capacity of a place, a more rigorous model of government plans remains a gap in this study and further work should be done to better describe variances in this indicator.
GDP and internet access were the most sensitive indicators in the UACI as the indicators that changed most dramatically during the baseline period. These two indicators grew quickly within the range of the 10 point scores, and were also responsible for the fall in UACI scores after time, as they quickly maxed out as land became more urbanized, meaning their benefits peaked earlier in the timeframe in these two particular sites.
Another weakness of this study is the question of extrapolation. With several indicators urbanization is correlated with a positive or negative trend, but as it is often
stated, correlation does not equal causation. Many of the factors may not have a linear relationship with urbanization, or the relationship curve may change as time goes on.
Despite these flaws the results do reflect, on a larger level, several trends associated with urbanization and land use change. Taiwan has seen very clear climatic changes linked to global climate change which are more severe than in many other larger or inland countries. The changes in LULC have direct impacts on the adaptive capacity of Tamsui, particularly in terms of surface water stability. These are shown
clearly in the biophysical indicator results of the UACI. The government and public are both growing in awareness of the precarious nature of the island’s ecosystems to further
disturbance, and hopefully will enact more protections.
In terms of the socioeconomic aspects, Tamsui –in fact all of Taiwanese society –is indeed affected by wage stagnation despite the fact that urban areas of Taiwan do
have higher incomes than rural areas. It is still true that there remains an urban-rural disparity in wages, however, further development in cities or suburban areas may not necessarily lead to proportional increases in income in Taiwan. Unless there is major policy change in the near future, urbanizing will not necessarily bring the expected benefits to individuals and households, which will limit adaptive capacity.
West Palm Beach, on the other hand, is a more development-driven community and its public is much less likely to believe that climate change is occurring, potentially
weakening political will to address climate-related issues. But the indicators showed that it is less affected by temperature changes than Tamsui, which may partially account for the complacency. Its weaknesses in adaptive capacity lie in high inequality and a larger impervious surface ratio which are likely to be exacerbated by further urbanization, but West Palm Beach also stands to benefit from more urbanization with internet, GDP, and income indicators. These socioeconomic indicators are ones that increase more steeply with urban change. But to rely too heavily on technological or economic growth for AC would be unwise in the long term, and could be considered a kind of maladaption.
Another question of maladaption would be the increased developmental density near the water. Both sites are coastal, and development is concentrated near the ocean and will only intensify across all scenarios. This higher population density may alleviate the expansion of urban sprawl but simultaneously increases risk of health and economic loss in the event of a hurricane or typhoon or other flooding events. This tension is a difficult challenge for planners and policy makers and these different risks will need attention.