Modelling for prediction of global deforestation based on the
growth of human population
Krishna Pahari
), Shunji Murai
Institute of Industrial Science, UniÕersity of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo, Japan
Received 18 June 1998; accepted 16 February 1999
Abstract
Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms.q1999 Elsevier Science B.V. All rights reserved.
Keywords: forest loss; remote sensing; population density; population-deforestation model; global land cover change; AVHRR
1. Introduction
Global land cover change, particularly from forest to other land cover types due to increased human activity, is one of the most important issues in global change research. It has been especially remarkable in the last few decades, which witnessed an increasing rate of deforestation due to pressure caused by the population growth. Since forest is so vital for the sustenance of the ecosystem to which we belong, it
) Corresponding author. Fax: q81-3-5452-6408; E-mail: [email protected]
is becoming increasingly important to make predic-tions about the state of forest in the future under different scenarios to suggest appropriate policy measures.
Even though significant progress has been made in global change research in recent years, the lack of a reliable spatial dataset on deforestation continues to be a major obstacle for modelling global change ŽMurai, 1995 . However, it is still possible to analyse. the trends of global environment, including defor-estation with the existing satellites, meteorological and socio-economic data. In this study, deforestation is addressed relating it to population density and predictions are made about future deforestation, based on a projected population growth.
0924-2716r99r$ - see front matterq1999 Elsevier Science B.V. All rights reserved.
Ž .
Ž
Fig. 1. Historical trend of world population and projection source:
.
UNPD, 1994 .
There are several factors that seem to be related to deforestation, namely population, GNP, government policy, land ownership, etc. However, it has been found by the authors in the study that population is the most significant factor in global deforestation.
Human population has grown significantly in the last few centuries and has been especially alarming over the last several decades. Fig. 1 shows the historical trends of world population and future pro-jections, based on UN medium variant population
Ž .
scenario UNPD, 1994 . Obviously, this projection, if correct, is bound to have a tremendous impact on earth resources, including forest.
Fig. 2 shows the general framework of methodol-ogy followed in this study. Details of the various steps are discussed in the following sections.
2. Actual and potential natural land cover
It is now possible to monitor the global land cover with satellite data, particularly NOAA Global
Vege-Ž .
tation Index GVI data. Even though developing an accurate global land cover map is still an ongoing process by several researchers and projects, global land cover maps are now available and provide a good global overview. Fig. 3 presents an updated version of the global land cover map from Murai and
Ž .
Honda 1991 revised using the AARS 4-min grid
Ž .
dataset on global land cover AARS, 1997 .
Since land cover change has been occurring over a long time and satellite data for global monitoring have been available only for the last 15 years, a potential natural land cover map has been developed to simulate the land cover map prior to human activities, based on climatic data. Fig. 4 shows the potential natural land cover map, based on De
Mar-Ž .
tonne’s aridity index AI and the classification cate-Ž
gories introduced in Table 1 based on modified .
criteria by Murai and Honda, 1991 . The AI is defined as:
Pi
AI s ,
Ž
.
iTiq10
Ž .
where P is the total annual precipitation in mmi
Ž .
observed in cell i and Ti in degrees Celsius is the annual sum of monthly mean temperatures of those
Ž . Ž .
Fig. 3. Global land cover map for 1990 from NOAA GVI data, based on Murai and Honda 1991 and AARS 1997 .
months with monthly mean temperature greater than 0, divided by 12, for cell i.
Global rainfall and monthly mean temperature Ž
data interpolated into a surface grid of 10 min
.
resolution for the last 30 years were obtained from the University of Tokyo.
Based on the above analysis, Table 2 shows the results of potential natural land cover and actual land
Table 1
Ž . Ž .
Aridity index AI and land cover types Murai and Honda, 1991
Land Cover Types AI
Desert F5
Semi-desert 5-AIF10
Grassland 10-AIF20
Forest )20
Ž .
cover for 1990 on a global level. The table shows that humans deforested 15.3% of the potential forest area and increased the potential area covered by deserts and semi-deserts by about 14.8%.
3. Population-deforestation model
Out of several correlation analyses studied by the Ž
authors such as GNP and deforestation, several . combinations of population and deforestation , it was found that the correlation between the logarithm of population density and the cumulative forest loss computed from potential natural land cover and ac-tual land cover was most significant. More specifi-cally, the correlation of GNP per capita with forest loss was very low in all tested areas.
Due to the unavailability of detailed historical data about the global forests over a fairly long period to conduct trend analysis and to make projections, cross-country data obtained by grouping countries with similar ecoclimatic zones and similar stages of economic development have been used to develop the model introduced in this paper.
Although Fig. 3 provides a good global overview of forest and other land covers and fits globally with the FAO forest statistics, the authors concluded that FAO’s statistics led to more reliable estimates of the forest cover for individual countries.
Table 2
Ž .
Percentage of potential and actual 1990 global land cover Land cover Potential Actual Change from
type area area original
Forest 48.46 33.20 y15.26
Grassland 34.27 34.73 q0.46
Semi-desert 8.36 15.79 q7.43
Desert 8.91 16.28 q7.37
Table 3
Ž
Cumulative forest loss in selected countries forest cover in 1990,
.
based on FAO, 1997
Country Potential Forest cover Cumulative forest
Ž . Ž
forest in 1990 loss % column
Ž .% Ž .% 2ycolumn 3r
.
column 2
Brazil 97.54 66.68 31.64
Peru 91.95 53.63 41.67
Bolivia 92.39 47.22 48.89
Ghana 100.00 42.23 57.77
Cameroon 97.88 43.50 55.56
Zimbabwe 74.84 23.16 69.05
Bangladesh 100.00 8.10 91.90
Thailand 99.53 25.99 73.89
Malaysia 97.27 53.18 45.33
India 82.28 21.85 73.44
Nepal 83.81 37.25 55.55
Former USSR 41.87 37.96 9.34
France 99.28 25.87 73.94
UK 98.98 9.63 90.27
In this study, the cumulative forest loss for each country was computed as the total forest loss
ob-Ž .
served from the potential land cover map Fig. 4 and the current forest cover for 1990, based on FAO forest statistics.
A regression analysis was conducted using the logarithm of population density as independent able and cumulative forest loss as dependent vari-able. The countries were grouped into regions, based on similar ecoclimatic zones and level of socio-eco-nomic development.
Table 3 presents the cumulative forest loss for selected countries. Table 4 gives a summary of the correlation index between natural logarithm of
popu-Table 4
Correlation between population density and cumulative forest loss for different regions
2
Region Regression function R
Ž .
Tropical Asia 16.042 ln xy19.56 0.638
Ž .
Tropical Africa 15.206 ln xq7.8446 0.717
Ž .
Sahelian Africa 16.872 ln xq12.305 0.638
Ž .
Tropical Latin America 16.896 ln xy7.020 0.672
Ž .
Central America and Mexico 21.637 ln xy29.643 0.824
Ž .
lation density and cumulative forest loss for various regions. Fig. 5 shows the scatterplots for population
Ž . Ž .
density logarithm and cumulative or total forest loss for various regions.
Ž 2 . Ž . Ž . Ž .
Fig. 5. Scatterplot between population density personsrkm , logarithm and cumulative forest loss % for a Tropical Asia; b Tropical
Ž . Ž . Ž . Ž .
Ž . Ž 2. Fig. 6. a Historical trends of population density personsrkm
Ž . Ž
and forest cover % of total land in Thailand forest cover, mainly based on Mather, 1990 and population density, based on
. Ž .
Statistical Year Books of Thailand . b Analysis of historical
Ž
trends of population density and deforestation in Thailand 1949–
.
1991 .
In order to see that such linkages between popula-tion density and forest loss hold true for time series analysis for a given country, this method has been tested using time series data of population density and forest cover of Thailand. Fig. 6a and b show the results of such analysis for Thailand linking popula-tion density and the total forest loss and it shows that
Ž 2 .
there indeed exists a high correlation R s0.9736 between logarithm of population density and cumula-tive forest loss.
4. Predictions for deforestation
Having established the population-deforestation model presented above, predictions have been made for the future state of deforestation. Deforestation for years 2025 and 2050 was estimated for each country by using the population-deforestation model and the projected population density, based on UN medium
Ž variant long-range population projections UN,
.
1997 , and then the annual deforestation rates d andi the forest loss L since 1990 were calculated byi using the 1990 forest cover and the predicted forest covers for 2025 and 2050 as:
LŽ1990 – 2025.
and similarly for 2050. Table 5 shows the results of such predictions for different regions.
It can be seen from Table 5 that the deforestation scenario is most serious for Tropical Africa, fol-lowed by Sahelian Africa, central America, Tropical Asia and Tropical Latin America. The African region is also the area where the population is projected to increase most rapidly in the coming years.
The predicted deforestation map for any year, say 2025, is then simulated using the following steps.
Ž .1 The land cover map for 1990, as presented in Fig. 3, is used as the starting point.
Table 5
Scenario of deforestation from 1990 to 2025 and from 2025 to 2050
Ž . Ž . Ž .
Region Forest coverage 1990 % Predicted annual deforestation rate % Forest loss since 1990 %
1990–2025 2025–2050 2025 2050
Tropical Asia 34.81 0.55 0.30 17.44 23.39
Tropical Africa 36.94 1.15 0.68 33.27 43.67
Sahelian Africa 13.52 1.00 0.43 29.62 36.87
Tropical Latin America 61.24 0.37 0.29 12.03 18.29
Central America 31.58 0.65 0.39 20.50 27.87
Europe 36.78 0.01 0.00 0.26 0.26
Fig. 7. Map showing prediction of deforestation from 1990 to 2025.
Ž .2 Based on the gridded population density map
Ž .
of the world for 1994 CIESIN, 1996 , and using the UN medium variant population projections for each country, a map is prepared for the predicted
popula-Ž tion density for the year under consideration here,
. 2025 and 2050 .
Ž .3 From the map of 1990 land cover, the cells
Ž .
with the highest population density from step 2 for each country are then assigned a new land cover class from forest to non-forest such that the total number of cells so converted is equal to the total predicted forest loss for that country.
Fig. 7 displays the predicted map of deforestation for the period 1990–2025, generated by using the above procedure.
5. Discussion of results
If we compare the predicted rates of deforestation in the next five decades, it appears that deforestation is going to be a significant problem especially in the developing countries of the tropical region. How-ever, the speed of deforestation is likely to be less compared to the peak period of 1980s. This con-forms with the trends of population growth, as there
are signs that the population growth is now actually slowing in many parts of the world, even though it is still going to be very significant. One exception to this is Africa, where the population growth is still picking up and is projected to slow down only after the next few decades. That is why the deforestation rate in Tropical Africa is likely to be most serious in the next several decades.
While there is some hope in the sense that the rate of deforestation is expected to slow down in most part of the world, however, if we consider the avail-ability of forest resources for the increasing popula-tion, the situation looks very serious. Table 6 shows
Table 6
Projected forest area per capita
Ž .
Region Forest area per capita ha
1990 2025 2050
Tropical Asia 0.19 0.09 0.08
Tropical Africa 1.35 0.36 0.22
Tropical South America 3.46 1.94 1.56 Central AmericarMexico 0.58 0.29 0.22
Tropical average 0.72 0.33 0.25
Sahelian Africa 0.74 0.20 0.13
Europe 1.24 1.24 1.24
the projected forest area per capita for different regions until 2050. It is a matter of further investiga-tions as to what are the requirements of forest area per person for healthy and environmentally sound living conditions. However, one thing that is very clear is that the availability of forest per person will decrease very drastically, especially in the develop-ing countries, which is likely to pose a major chal-lenge for human well-being.
6. Conclusions
The authors have established a model for linking population density with the deforestation, to predict the future state of deforestation. It is seen that even though the rate of deforestation is somewhat decreas-ing, deforestation will continue to be a significant problem in the next several decades, especially in the developing countries of the tropical region. Africa is likely to have the most rapid deforestation followed by Tropical Central America, Tropical Asia and Tropical Latin America. The situation looks very serious in terms of forest resources available per capita in developing countries.
Although forest loss is caused by various factors including the market of forestry exploitation, and thus forest loss in certain regions may not be directly related to the population increase, the above analysis of the global trend as a whole, shows that in general, deforestation is highly correlated with the logarithm of population density.
Further work on global deforestation modelling, using more accurate datasets as they become
avail-able and possibly incorporating other factors such as GNP into the model, is being considered for future research. Another topic of future works is the
estab-Ž .
lishment of some thresholds refraining destruction to minimise the projected tendency of forest loss. The authors are also working on other aspects of global environment related to global deforestation, such as carbon fixation, primary productivity, carry-ing capacity, etc.
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