 |
|
Introduction / setting |
|
|
|
|
Introduction
"Just constructing dykes along all threatened coasts may, of course, not
be a good idea" (CZMS 1990, page 86)
By the "worst case" scenario, global mean sea-level is expected to rise
95 cm by the year 2100, with large local differences due to tides, wind
and atmospheric pressure patterns, changes in ocean circulation, vertical
movements of continents etc.; the most likely value is in the range from
38 to 55 cm (Warrick et al, 1996). The relative change of sea and land
is the main factor: some areas may experience sea level drop in cases
where land is rising faster than sea level. In addition, according to
a study by Titus and Narayanan, quoted by CZMS (1992), the statistical
distribution of sea-level rise exhibits a marked positive skew (i.e.
many average values and some very large ones in only a few locations).
Regarding human settlements, Scott (1996) expresses the view that the
impacts of sea-level rise and extreme events are likely to be experienced
indirectly through effects on other sectors - for instance changes in water
supply, agricultural productivity (Brinkman, 1995) and human migration.
Considering, in addition, that it is uncertain whether extreme events
associated with oceans will change in intensity and frequency (Venugopalan
Ittekkot, 1996; Nicholls et al, 1996), it seems likely that the internal
dynamics of human demography, coupled with a series of indirect factors,
including health factors (WHO, 1996), may eventually play a dominant part [1].
According to Nicholls (1995) quoted by WHO (1996), the majority of the
people that would be affected under the worst scenario live in China
(72 million) and in Bangladesh (71 million). Between 0.3% (Venezuela)
and 100% (Kiribati and the Marshall islands) of the population would
be affected. It is worth noting, however, that population per se receives
relatively little attention in the literature as compared, for instance,
to natural ecosystems or agriculture.
A disaster results from the impact of an extreme physical event on a
vulnerable society or human activity (Susman et al, 1983). Disasters
can be quantified and predicted only insofar as the factors of the
product "extreme event x vulnerable system" are reasonably well known
and quantified. In the specific case of sea-level rise (SLR) and
population, only some terms of the equation are known: at the macro
level, population growth is affected by the least error, but details
of future population distribution, as well as the level of urbanization,
are more open to debate, especially as to whether the future concentration
of population will coincide with the area corresponding to the large
positive skew referred to above. The vulnerable system itself is
currently difficult to describe at the global level, for two reasons.
First, sufficiently detailed digital maps of elevation, crops and
population are not available; second, the future dynamics of the
response of coasts, coastal human activities and populations is
largely open to debate. As to future impacts around years 2050 or
2100, we are not in a position either to describe with any level
of accuracy and confidence what the impacted systems will be like
because, inter alia, both the coastal landscape and buildings and
infrastructure will adapt gradually in response to the changing
environment and the socio-economic driving forces.
The main weaknesses are thus in the sea-level rise predictions, as
well as the interactions with human activities.
The general demographic,
physiographic and socio-economic setting
Contrary to a common assertion [2] according to which "it is estimated
that 50-70% of the global human population lives in the coastal zone"
(IPCC 1996b, p. 294), the population is rather land-bound, as illustrated
in Table 1 below. The densities given are approximate in that they are
based on an assumed total length of the coastline of 100,000 km and on
"large, round" continents. Global population density is about 39 persons/km2.
In spite of the gross approximations involved in the last column of
Table 1, it is clear that population densities are far higher along the
coasts than inland. Small (personal communication) indicates the
percentages to be 37% within 100 km, and 66% within 400 km.
Table 1. Distribution
of world population as a function of the distance from the nearest
coastline
| Distance from the coast(km) | Population (million) | Accumulated population (million) |
Accumulated percentage | Approximate density (people km-2) |
| up to 30 | 1147 | 1147 |
20.6 | 382 |
| >30 to 60 | 480 | 1627 |
29.2 | 160 |
| >60 to 90 | 327 | 1954 |
35.0 | |
| >90 to 120 | 251 | 2205 |
39.5 | |
| beyond 120 | 3362 | 5567 |
100 | |
Based on the digital vector map by Tobler et al. (1995 and 1997),
roughly 1:5 M scale, population standardized to 1994.
There are, of course, large local differences. For instance, Sestini (1992;
quoted by Zwick 1997), writes that: "the importance of the Mediterranean
seafront in relation to the rest of the country varies; as an example, it
is relatively less so in Spain, France and Turkey than in Italy, Greece,
Albania, Algeria, Israel. In Greece as much as 90% of the population lives
within 50 km of the coast and all major industrial centres are coast-related
as well as much of agriculture. In Egypt, the Nile delta north of Cairo
represents 2.3% of the area of the country, but contains 46% of its total
cultivated surface and 50% of its population; the [altitude] belt 0-3 m
harbours about 20 % of the population (with Alexandria 3.5 mill., and
Port Said 450.000 inhabitants), 40% of industry, 80% of port facilities,
60% of fish production." As a whole, world population, now at 5,880 million,
is expected to begin levelling off around 2050 at about 9,300 to 9400 million
people (middle estimates of UN 1996a and 1996b), although in some continents,
notably Africa, population will probably continue growing at a more sustained
pace well into the 21st century. The urbanized population should exceed 60%
of the total in 2030, from current values of around 50%.
Figure 1. Recent
and future population and urbanization trends (based on data from
UN 1996a, 1996b and 1997)
It is also well known that most of the current largest urban concentrations [3]
are on the seacoasts (Engelman 1997). The population in the world's 15 biggest
cities is projected to be 223 million in the year 2000. It appears that overall
urban population trends are not so obvious. While most coastal megacities do
grow in size, their share of the total population often remains stable (1%,
from 1950 to 2015 in Calcutta and Shanghai), and sometimes decreases (from 7%
to 6% in New York in the same period. Also, the percentage of the urban
population living in the megacities often decreases (New York: 12% to 7%
between 1950 and 2015; Cairo: 35% to 32%; Rio de Janeiro: 14% to 6%; Calcutta:
7% to 4%; Beijing: 6% to 2%; Jakarta: 15% to 10%, etc.), which points to the
growth of other urban areas.
Also noteworthy is the fact that many cities suffer land subsidence due to
groundwater withdrawal (Nicholls and Leatherman, 1995). This, of course, may
be compounded by sea-level rise, the more so since current rates of subsidence
may exceed the rate of sea-level rise between now and 2100.
Table 2 below indicates how some socio-economic and physiographic indicators
vary among land-locked countries, those with coastlines and the smallest
islands, which are members of the Alliance of Small Island States (AOSIS).
It is striking that the average Gross Domestic Product (GDP) per capita in
landlocked countries is just above that of AOSIS members, and well below the
global average. It is also worth noting that the population densities of the
small island states are currently intermediate between landlocked and "other"
countries, while they should reach a value comparable to "other" countries in
2050. It is unlikely that this will be accompanied by a marked increase in GDP
per capita.
Table 2. Some general
statistics about landlocked countries and territories and AOSIS member
states (see list in Appendix)
| | Number |
Area 000 km2 | Arable Land % |
GDP/ Capita US$ (1996) | GDP US$ (1996) |
Population (1995) Million |
Pop. density (1995) | Pop. density (2050) |
Coastline length Km |
| Landlocked | 44 |
378 | 13.8 |
4711 | 9.44E+11 |
348 | 126 |
128 | 0 |
| AOSIS | 32 |
9.34 | 17.2 |
4518 | 1.06E+11 |
37 | 252 |
538 | 1091 |
| Others | 154 |
83.4 | 13.0 |
7829 | 3.26E+13 |
5325 | 468 |
577 | 5144 |
| Average | |
129 | 13.8 |
6772 | |
| 372 |
486 | |
| Total | 230 |
| |
| 3.36E+13 |
5710 | |
| |
"Others" stands for countries that have a direct access to the ocean but
are not AOSIS members. All data from Factbook (1997), except population
statistics taken from UN 1996a, 1996b and 1997.
In order to examine with more detail the relation between some of the
indicators in Table 2 and the "insularity" of the respective countries,
we define an "Insularity Index" as the ratio between the length of the
coastline (km) and the total land area (km2) that it encloses:
| Insularity Index = |
Coastline |
| -------------- |
| Land area |
The definition of The "Insularity Index" is, of course, fraught with problems
[4] linked with the actual shape of countries, the fractal nature of coasts,
and the scale at which it is determined, and the distribution and extent of
low-lying areas within each country. It is admittedly a crude index, but
meaningful if a consistent method is used to estimate the length of the
coastlines. Some interesting links with other variables can be found at
the global level. Table 6 lists some typical values of The Insularity Index.
It is obvious, to start with, that Europe and Africa - which represent 50%
of all countries and territories - are far less "insular" than the other
continents. It is also apparent that the insular character has a strong
positive skew and covers 5 to 6 orders of magnitude, to the extent that
it can be represented only on a logarithmic scale. The positive skew is
clearly visible in Table 3, in which the large difference between median
and average is due to the occurrence of a limited number of very high values.
Table 3. The Insularity
Index for various countries and territories grouped by "continents".
| | America (NS) |
Asia, Australia | Europe, Africa |
Global |
| Countries* | 57 |
46 | 121 | 224 |
| Average | 0.411 | 0.611 |
0.0772 | 0.272 |
| Median | 0.0944 | 0.0226 |
0.00234 | 0.00770 |
* The different numbers of countries given in different table are due
to missing data in the original data sets. The landlocked countries
are included in the statistics (there are 2, 9 and 31 landlocked
countries, respectively, in the America, Asia and Australia, and
Europe and Africa groups). "America" covers the area west of 30
western longitude (30W) and 180W; "Europe and Africa" spans the
longitudes from 30W to 60E, and "Asia and Australia" go from 60E to 180E.
The Pacific Islands (roughly from 145E to 109W at equatorial latitudes)
are included under "America" and "Asia and Australia". The data used
to compute the Insularity Index values are from Factbook (1997).
The two figures below clearly show the association between the insular
character of countries and population density: less insular countries
are generally relatively less populated, which is linked to the fact
that landlocked countries are mostly at higher elevations and latitudes
(Eurasia) or in semi-arid areas (Africa) where productivity and population
supporting capacities tend to be low.
Figure 2. Variation
of current population density (1995) as a function of the Insularity Index
Based on 192 countries and territories for which the data are available
in UN 1996a and UN 1997 (population data) and in Factbook, 1997, for the
computation of the Insularity Index.
In a similar way, and as a consequence of the situation described previously,
GDP tends to decrease with insularity, mostly so above a "threshold" of 0.01.
Figure 3a. Variation of
1996 Gross Domestic Product (GDP) and GDP/capita as a function of Insularity Index
Figure 3b. Variation
of 1996 Gross Domestic Product (GDP) and GDP/capita as a function of Insularity
Index
Based on data from Factbook, 1997.
Notes
1. Direct effects can be assumed to more significant in the ecological
sphere (see, for instance Bijlsma, L. 1996).
2. The statement is ubiquitous, with many variants, including "By some
estimates, nearly two-thirds of the world's population lives within
100 miles of an ocean, inland sea or major freshwater lake" (Engelman,
1997, p 39), or "Six out of ten people live within 60 km of coastal waters"
(IUCN, 1991, p. 150) or "At present, six out of 10 people live within 60
km of the coast" (FAO, 1997).
3. They include, in decreasing order of the projected population in the
year 2000: Tokyo, Mexico City, Bombay, Sao Paulo, New York, Shanghai,
Lagos, Los Angeles, Calcutta, Buenos Aires, Seoul, Beijing, Karachi,
Delhi and Dhaka (UN, 1997).
4. For instance, the Factbook (1997) indicates 14,500 km for China (without
Taiwan), but Du (1993), quoted by CGER (1996) uses 18,700 km (including
Taiwan). India has 7,000 km in both CGER (1996, quoting Asian Development
Bank) and Factbook (1997), while CZMS (1990) indicates 3,280 for the length
of the coast "as the crow flies" with a step of 50 to 100 km. The same
source applies a multiplier of 10 to obtain 32,440 km of "length of low
coast", i.e. the actual length of coast that should be protected, taking
into consideration its "micro" structure. For Vietnam, the figures are
3,260, 3,444, 512 and 6,095 (respectively CGER, Factbook, CZMS with and
without multiplier). For Japan, the figures 29,751, 34,390, 530 and 3,870
are obtained by the same sources. Regarding the total length of all coasts
(excluding Antarctica), we found 642,770 based on a 1:25M map, while the
data from the Factbook (1997) add up to 715,917. Annex D2 of CZMS (1990)
finds 46,185 km using 50 to 100 km "steps" and 339,185 km of "low coast".
|
 |