DEFINITION
OF LOW FOREST COVER (LFC)
Developed by UNEP and IUFRO
Coordinated by:
H. Gyde Lund
Forest Information Services
6238 Settlers Trail Place
Gainesville, VA 20155-1374 USA
Voice: +1-703-743-1755, Fax: +1-703-743-1756
Email: gyde@comcast.net
URL: http://home.comcast.net/~gyde/index.html
Abstract: The Intergovernmental Forum on
Forests (IFF) identified countries of Low Forest Cover (LFC) as being of
special concern. Unfortunately, a definition of LFC was not available. It
called on UNEP, as lead agency for this programme element, to expedite the
development of a definition of low forest cover as contained in IPF's proposals
for action. Following a subsequent request by UNEP, the International Union of
Forestry Research Organizations (IUFRO) requested that its members undertake a
short-term study to develop a definition of LFC. Definitions of
"forest", thresholds and data availability are additional concerns
This paper covers some of the problems involved with developing a definition
and offers four different options. An eigenvalue analysis indicates that the
classifications of countries based upon a combination of variables (area of
Forest and Other Wooded Lands, Original Forest Land, and Population) is a good
first attempt. Intent of actions and data availability will dictate what
definitions and thresholds to use.
Keywords: Forest, Low Forest Cover, Original
Forest, Forest and Other Wooded Lands
Cite as: Lund, H.
Gyde. 1999. Definition of Low Forest Cover (LFC). Report prepared for
IUFRO. Manassas, VA. Forest Information Services. 22 p. Online at http://home.comcast.net/~gyde/LFCreport.html
INTRODUCTION
The Intergovernmental Forum
on Forests (IFF) recognized that there are both developed and developing
countries with low forest cover. Low forest cover can arise as a result of
natural ecological conditions, as well as of human activities and the situation
is constantly changing. Some countries are actively expanding their forest
cover, while others are approaching qualification for entry into the low forest
category.
The restricted area of
forests in countries with low forest cover results in reduced capacity for the
production of timber and for the provision of goods and services, including the
protection of watersheds, the supply of fuelwood, the maintenance of biological
diversity and endemic species, and recreation and amenity. Moreover, many of
the forest types in those countries are distinctive or even rare, and require
national protective measures and international support, while the proportion
included in nationally designated protected areas is often below average.
The International Union of
Forestry Research Organizations (IUFRO) entered into a Memorandum of
Understanding signed with the United Nations Environment Programme (UNEP) for
the development of a workable and precise definition of low forest cover in
agreement with the Food and Agriculture Organization of the United Nations
(FAO). The definition was scheduled to be ready for IFF III in Geneva in May
1999 and would be introduced by UNEP as an IUFRO contribution. The definition
would be applicable to all countries and suitable for use in the forest
resource assessment in the year 2000.
The IUFRO Secretariat asked
Research Group 4.02 "Forest Resource Inventory and Monitoring" to
take on the job and prepare a report entitled "Countries with Low Forest
Cover" containing: a workable and precise definition of the term low
forest cover, applicable to all countries and suited for use in the forest
resources assessment in the year 2000; a list of countries with low forest
cover, based on the definition, option/ways for improving the productivity,
conservation and monitoring of countries with low forest cover, taking into
account the social and cultural dimensions. The deadline for the report was
November 30, 1998.
IUFRO's SilvaVoc project
and Working Party 6.03.02 "Trends in Forest Terminology" provided
assistance by compiling information on existing definitions and by setting up a
short-term discussion to provide additional "food for thought"
between 4 Nov 1998 - Dec 1998 (See http://www.NRCan.gc.ca/hypermail/lfc/)
On 27 Nov 1998, IUFRO 4.02
developed a "strawman" document and placed it on the web. IUFRO 4.02
announced the draft report's availability to various forestry lists and invited
comments and suggestions for change.
Based upon the comments
received, IUFRO 4.02 revised the document and sent the final on to IUFRO HQ on
6 Dec. 98.
IUFRO HQ forwarded the
draft to UNEP. Dr. Bai-Mass Taal, modified the draft and sent the revision out
for additional review in July 1999. Reviewers included L. S. Botero,
Coordinator FODA; Reidar Persson, CGIAR; and IFF Secretariat Tage Michaelson.
The UNEP draft was also
discussed at the International Meeting of Experts on Special Needs and
Requirements of Developing Countries with Low Forest Cover and Unique Types
held 4-8 October 1999 in Tehran, Iran. The Iran meeting resulted in a Tehran
Declaration (Anon. 1999) which asked for further work on the definitions. The
UNEP draft was revised, presented, and discussed at a Side Event meeting during
IFF 4 in New York City 2 February 2000. This paper includes all recommendations
to date.
GENERAL FINDINGS
Based upon the information
we can only make some general observations at this time. We need more
information as to why we are producing the definition. It seems that the
purpose of having and applying the definition is to allow someone (policy and
decision-makers where ever) to take action when forest cover is deemed to be
'low' for a country. The action could be internal to the country
(remedial action to prevent further loss, action to extend forests, actions to
address consequential problems of an environmental and or social nature), or
they could be taken external to a country such as pressure to limit access to
trade in forest products (exports) such as consumer pressure to limit sales or
purchases of products from LFC countries, etc.
1. Definitions: We can identify one or more
definitions of what LFC could be and how to calculate and report it, and how to
qualify it. However, understanding the purpose of the definition is important,
because the technical / scientific expertise which can be brought to bear, can
be used to produce many definitions which may serve some purposes better than
others Producing a definition of LFC, which seems to have at its core,
the need/ wish to take action to change how forests are used, will be even more
difficult. Once a country is labeled as an LFC, it may be delighted
because it may be an additional lever with which to obtain greatly needed
resources, or it may be offended because it sees itself being controlled unduly
by the nasty world outside.
Definitions suggested
during the review process included:
- Low timber trade to countries with high trade
- Ratio of open forest to closed forest
- Ratio of coppice forest to high forest
- Ratio of areas with short trees to areas with tall
trees
- The ratio of forest (or forest and other wooded
lands (FOWL)) to total land area
- Areas where lack of forest cover is damaging ecological
process
- The ratio of forest or FOWL to original
forestland
- The ratio of forest or FOWL per capita
- Forestland to high number of people having hardships in
these areas
Option 1 focuses on
economics and not necessarily ecological needs of countries. Options 1-5 strive
to make all countries equal. Ecologically not all countries can have the same
amount and types of forestland. Cyprus cannot have the same size trees as
California and Qatar cannot have the same amount of forestland as Finland.
Options 6 and 7 are very
similar. They are based upon what may be ecologically possible. Data are
easiest to come by for option 7.
Options 8 and 9 are also
similar based upon needs of the local people - this is also an indication of
the amount of pressure that may be place on any remaining or soon to be
established forest lands. Data for option 8 are more easily obtained and less
subjective than those for option 9.
Basically options 7 and 8
or a combination of the two are most feasible and most likely to address the
concerns of the IFF.
Those options in bold
(Nos. 5,7, and 8) are discussed in detail in this report. Each presents a
different picture and requires different information.
2. Thresholds: Thresholds are the
numbers for determining whether a country qualifies as a LFC or not. Thresholds
generally have a predefined set of conditions. These conditions occurred before
the threshold, but not after, based on given variable(s). You may use a
threshold only under these conditions and only when these variable(s) are
present to show that conditions have changed after the threshold.
There are two ways of
specifying a threshold. One is based on an arbitrary percent of countries
falling below a certain line and the other is based upon some
"scientific" gateway. The maps and tables in this report illustrate
how different definitions and thresholds affect what is considered LFC. All
data are from Appendix 1. Note, we did not have data for Antarctica, Greenland,
Oman and Western Sahara.
Arbitrary percent - Thresholds for determining whether
a country qualifies as a LFC may be based upon an arbitrary percent. For example
the bottom 25 % of countries having the lowest ratio of forest to original
forest cover (figure 1) or the bottom 25% of countries having the least amount
of forestland or FOWL per capita (figure 2). The 46 countries in white (figure
1) have less than 19% of their original forest cover left.
The 76 countries in white,
figure 2, have less than 0.3 percent of FOWL per capita. The breakdowns can be
modified - i.e. the bottom 10%, 33%, etc. using MS Excel.
Scientific thresholds - Conservation groups recommend
that at least 10% of a nation's forestland be protected. Therefore countries
having less than 10% of original forestland left may be considered as LFC from
an ecological perspective. Figure 3 shows the 30 countries (shaded) having 10%
or less original forestland remaining.
As with the definitions, we
need to get much greater clarification of just what the LFC figures are
expected to be used for so that our efforts to set a threshold can be informed,
rather than totally arbitrary; and can be focused on the kinds of outcomes that
are desired.
Data availability: FAO has good harmonized estimates of
forestland and forest and other wooded lands (FOWL). They also have good
estimates of total land area and population per country. These data are
currently being updated for the Global Forest Resource Assessment 2000 (FRA
2000). The World Conservation and Monitoring Centre and the World Resources
Institute have estimates of "original" forest going back to 8000
years ago broken down on a country by country basis. The definition used for
"original" forest differs from what FAO uses for its Global Forest
Resources Assessment and, of course, no one knows for sure what was forested
8000 years ago. In spite of these shortcomings, the aforementioned forest data
sets are the only ones we have on a country by country basis for the entire
globe. A first cut at a global data set is given in Appendix 1. We either must
rely on these global databases or, as one contributor suggested, we ask each
country for to provide new data both on the current situation and on it's past.
The political difficulty
is, of course, to get countries to find the resources to put into the data
collection exercises initially. Even conducting reliable population censuses is
difficult for many of them despite the very long history of attempts at doing
it. Given the time frame specified by IUFRO, solicitation of
data on a country by country basis is not a viable option.
AN ANALYSIS OF POSSIBLE
DEFINITIONS
1. Ratio of forest cover
to total land area - Forest
area/land area- is a measure of environmental scarcity of forests. It is usable
in policy-making on the forest's impact on timber-production, national balances
on yield and cuttings, different environmental qualities, etc. It reflects the
importance of the forest in the landscape. The automatic inference of LFC is
that if there is "low" forest cover it is in relation to the total
land base. The advantage of the Forest area/land area ratio is that the data
are readily available from the FAO.
1.1 Thresholds: Options suggested include:
- Having least 25 percent of the total land area
forested.
- If the purpose were to document the amount of land area
occupied by forests it would be appropriate to compare the percentage of
forest in a country to the global average and categorize it as
"low" or "high".
- Using FAO's definition of forest, a low forest cover
country is one that has less than 7 % of its land area forested
- Using an arbitrary figure of 10 percent
1.2. Examples: Table 1 shows a listing of
countries having less than 10 percent forest and other wooded lands (FOWL). See
Appendix 1 for definitions and data. Table 2 shows a similar listing but only
for forestland. Note that most of the countries shown are arid and the
definition and delineation of forestland becomes more difficult. For this
reason, it may be preferable to consider FOWL instead of forestland.
|
Table 1- Listing of Countries having less than 10 percent
Forest and Other Wooded Land (FOWL) |
|
|
Country |
FOWL/ Total Area % |
|
Malta |
0.00 |
|
Egypt |
0.03 |
|
Kuwait |
0.28 |
|
Saudi Arabia |
0.42 |
|
Iraq |
0.44 |
|
Libya Arab Jamahiriya |
0.48 |
|
United Arab Emirates |
0.72 |
|
Lesotho |
0.76 |
|
Iceland |
1.47 |
|
Algeria |
1.66 |
|
Jordan |
1.95 |
|
Syrian Arab Republic |
2.63 |
|
Eritrea |
2.79 |
|
Tajikistan |
2.92 |
|
Yemen |
3.64 |
|
Tunisia |
3.66 |
|
Kyrgyzstan |
3.81 |
|
Kazakhstan |
3.93 |
|
Afghanistan |
4.01 |
|
Pakistan |
4.06 |
|
Mauritania |
4.42 |
|
Haiti |
5.04 |
|
Uruguay |
5.34 |
|
Israel |
6.01 |
|
Singapore |
6.56 |
|
Iran |
6.99 |
|
Turkmenistan |
7.99 |
|
Morocco |
8.08 |
|
Niger |
8.24 |
|
Swaziland |
8.49 |
|
Ireland |
8.58 |
|
Netherlands Antilles |
8.75 |
|
Mongolia |
8.77 |
|
Seychelles |
8.89 |
|
Netherlands |
9.99 |
|
Table 2 - Countries having less than 10% Forest Land/Total
Area |
|
|
Country |
Forest Land/ Total Area % |
|
Barbados |
0.00 |
|
Cayman Islands |
0.00 |
|
French Polynesia |
0.00 |
|
Malta |
0.00 |
|
Netherlands Antilles |
0.00 |
|
Yemen |
0.02 |
|
Egypt |
0.03 |
|
Saudi Arabia |
0.10 |
|
Iraq |
0.19 |
|
Lesotho |
0.20 |
|
Libya Arab Jamahiriya |
0.23 |
|
Kuwait |
0.28 |
|
Iceland |
0.34 |
|
Jordan |
0.51 |
|
Mauritania |
0.54 |
|
United Arab Emirates |
0.72 |
|
Haiti |
0.76 |
|
Algeria |
0.78 |
|
Iran |
0.94 |
|
Djibouti |
0.95 |
|
Tajikistan |
1.13 |
|
Syrian Arab Republic |
1.19 |
|
Somalia |
1.20 |
|
Niger |
2.02 |
|
Afghanistan |
2.14 |
|
Kenya |
2.27 |
|
Pakistan |
2.27 |
|
Eritrea |
2.79 |
|
Saint Helena |
3.23 |
|
Tunisia |
3.57 |
|
Kyrgyzstan |
3.81 |
|
Kazakhstan |
3.93 |
|
Comoros |
4.04 |
|
Uruguay |
4.66 |
|
Israel |
4.95 |
|
El Salvador |
5.07 |
|
Lebanon |
5.08 |
|
Australia |
5.35 |
|
Morocco |
5.39 |
|
Mauritius |
5.91 |
|
Mongolia |
6.00 |
|
Singapore |
6.56 |
|
South Africa |
6.96 |
|
Bangladesh |
7.76 |
|
Turkmenistan |
7.99 |
|
St. Lucia |
8.20 |
|
Swaziland |
8.49 |
|
Ireland |
8.58 |
|
Chad |
8.76 |
|
Seychelles |
8.89 |
|
Mali |
9.49 |
|
Rep. of Moldova |
9.76 |
|
Gambia |
9.80 |
|
Netherlands |
9.99 |
1.3 Implications: The implication by this definition
is very limited. All we can say is that the countries have low forest cover. A
disadvantage is that comparison might be misleading, because not all land is
potential forestland. A low forest cover, by this definition, is not a reduced
capacity, but only a low capacity. For example, a country occupying mostly
grassland will never have much forest. Australia (see Appendix 1) has a low % forest
cover, compared with Malaysia, but so what? The different climatic conditions
that cause huge deserts in Australia are the clear cause.
2. Ratio of current
forest area per capita - Forest area/capita is a measure or proxy of physical supply available to
match the human demand for forest goods and services. The ratio gives you an
idea of pressure; e.g. when there are lots of people there will most likely be
little forest and vice versa. High populations do tend to make higher demands
on forest resources and exert greater pressures on them. It is usable in
policy-making on afforestation for recreational and leisure activities in a
highly populated country like Denmark.
Demographic considerations
must be factored into any process aimed at determining priorities for natural
resource management. Population is only one of the factors-albeit a significant
one-driving natural resource depletion and degradation. The more important and
much more positive message is that programs that improve human well-being such
as family planning and education also have the enormous
"side-benefit" of helping to slow population growth, thereby reducing
its effect not only on forest loss and degradation but also on water quality,
agricultural demand, soil erosion, climate change, species loss, and a host of
other environmental/ecosystem issues.
2.1 Thresholds: Suggested options include:
1) Using FAO's less than
.07 ha of forest per person.
2) UNEP divided the
countries of the world into four groups based upon per capita forest area in
1990. 25 percent of the world's countries had less than .0l07 ha of forest
cover per capita. Rounding this up to 0.1 ha is a benchmark as
"critical minimum value … to supply all domestic (wood) needs" and as
an indicator of forest resource scarcity. Use the 0.1 ha as the lower limit of
modest to high levels of per capita forested land in each country. Below this
figure, countries are considered to have forest cover and therefore a scarcity
of forest resources.
3) Using a threshold base
on the average amount of forest and other wooded lands needed to support one
human being. Lund and Iremonger (1998) calculated a crude estimate of the
minimum FOWL/capita to be 0.73 ha.
2.2 Example: Table 3 shows the countries having
less than 0.73 ha of FOWL per capita.
|
Table 3 - Countries having less than 0.73 ha of Forest and
Other Wooded Land/Capita |
|
|
Country |
FOWL/ Capita |
|
Malta |
0.000 |
|
Egypt |
0.001 |
|
Singapore |
0.001 |
|
Kuwait |
0.003 |
|
Iraq |
0.009 |
|
Lesotho |
0.011 |
|
Bangladesh |
0.012 |
|
Haiti |
0.017 |
|
Barbados |
0.019 |
|
Israel |
0.021 |
|
Pakistan |
0.021 |
|
Netherlands |
0.022 |
|
United Arab Emirates |
0.025 |
|
Jordan |
0.027 |
|
Syrian Arab Republic |
0.032 |
|
Netherlands Antilles |
0.033 |
|
Mauritius |
0.039 |
|
United Kingdom |
0.042 |
|
Lebanon |
0.045 |
|
Saudi Arabia |
0.045 |
|
Seychelles |
0.053 |
|
Tunisia |
0.061 |
|
Comoros |
0.062 |
|
Belgium |
0.066 |
|
Tajikistan |
0.068 |
|
Eritrea |
0.079 |
|
Rep. of Moldova |
0.081 |
|
India |
0.084 |
|
Puerto Rico |
0.088 |
|
Armenia |
0.094 |
|
Denmark |
0.102 |
|
St. Vincent &
Grenadines |
0.107 |
|
Yemen |
0.114 |
|
Grenada |
0.118 |
|
Afghanistan |
0.122 |
|
Azerbaijan |
0.129 |
|
China |
0.129 |
|
Reunion |
0.130 |
|
Algeria |
0.131 |
|
Germany |
0.131 |
|
Korea, Rep. |
0.136 |
|
Rwanda |
0.143 |
|
El Salvador |
0.148 |
|
Swaziland |
0.153 |
|
Kyrgyzstan |
0.157 |
|
Libya Arab Jamahiriya |
0.158 |
|
Ireland |
0.161 |
|
Yugoslavia |
0.164 |
|
Switzerland |
0.169 |
|
Iran |
0.174 |
|
Hungary |
0.179 |
|
Martinique |
0.183 |
|
Trinidad and Tobago |
0.184 |
|
Philippines |
0.187 |
|
Ukraine |
0.187 |
|
Italy |
0.189 |
|
Dominican Republic |
0.192 |
|
Cayman Islands |
0.194 |
|
Japan |
0.196 |
|
Burundi |
0.204 |
|
Guadeloupe |
0.210 |
|
Morocco |
0.210 |
|
Luxembourg |
0.211 |
|
Sri Lanka |
0.217 |
|
Liechtenstein |
0.219 |
|
St. Lucia |
0.227 |
|
Poland |
0.231 |
|
Gambia |
0.233 |
|
Thailand |
0.248 |
|
British Virgin Islands |
0.250 |
|
Nepal |
0.252 |
|
Czech Republic |
0.256 |
|
Jamaica |
0.257 |
|
Uruguay |
0.284 |
|
France |
0.290 |
|
Cuba |
0.293 |
|
Romania |
0.297 |
|
Vietnam |
0.303 |
|
Korea, DPR |
0.316 |
|
Turkey |
0.321 |
|
Albania |
0.336 |
|
Portugal |
0.351 |
|
Malawi |
0.360 |
|
Cyprus |
0.363 |
|
Monserrat |
0.364 |
|
Slovakia |
0.378 |
|
Uzbekistan |
0.387 |
|
Antigua and Barbuda |
0.388 |
|
Costa Rica |
0.408 |
|
Macedonia |
0.449 |
|
Bulgaria |
0.468 |
|
Croatia |
0.470 |
|
Iceland |
0.471 |
|
Austria |
0.482 |
|
French Polynesia |
0.507 |
|
Slovenia |
0.540 |
|
Lithuania |
0.555 |
|
Kenya |
0.580 |
|
Georgia |
0.591 |
|
Greece |
0.614 |
|
St. Kitts and Nevis |
0.615 |
|
Nigeria |
0.617 |
|
Bahamas |
0.628 |
|
Kazakhstan |
0.644 |
|
Spain |
0.656 |
|
Indonesia |
0.703 |
|
Dominica |
0.704 |
|
Ethiopia |
0.704 |
Figure 4 shows the 106
countries (shaded) having less than 0.73 FOWL per capita.
2.3 Implications: The implication is that countries
that have below the threshold either need to increase their forest land to meet
their needs or import forest products. This criteria alone does not tell us if
a country has the land suitable for expanding their forest base.
Some countries, like Canada
and Russia (see Appendix 1), have huge forest areas and relatively low
populations, but this does not make their forests' products and services, or
especially their rare forested ecosystems, free from threats of
over-exploitation or poor practices. So, the stated purpose appears not to be
addressed by this indicator.
A main argument advanced
for using population is as an indirect comparison of forest area
with consumption of wood products, with the implication that Low
Forest Cover countries would be long-term large net importers, and that
this would be an undesirable state to remain in. But this ignores
differences in per capita consumption of wood products - if a country consumes
less wood, then it requires less forest to meet these needs. This also
ignores consumption of non-wood forest products - fuelwood etc. It also does not take account of the gains from international trade
- there is nothing wrong with a country specializing in, for
example, agriculture and trading with another specializing in timber.
3. Ratio of current
forest area to historic or potential forest area - This is a measure of land capability
to grow forest or forest resources forgone as it were. The latter can be
measured using potential vegetation maps. If the measure is to get at helping
to identify countries that could increase their forest cover, those that
haven't had much historically probably never will. Options include forests
prior to:
- Human influence (extending back to the beginnings of
agriculture, even hunting and gathering nomadic tribes in some areas).
- Set the date at around the beginnings of the Industrial
Revolution, when trade channels opened up, and the mechanization of new
ways to process resources allowed for improved and efficient harvesting.
This information could be obtained for various countries.
- Pre-Industry. Pre-Mechanization. For each country, the
date will be different, and should be. The date will depend on when the
timber industry really established itself (assuming it is present in the
country), or the agricultural industry (again, assuming it is present), or
whatever human influence first took a toll on the resource we know as
"forests", however defined by that country.
- Each country should determine and report on its current
area of forest, noting how it defined it. Using the FAO definition
would be advantageous, but would not be essential. Each country should
report on the area of forest against some specified historical time
line. 1750 could be the guideline, but for countries with capacity
to determine earlier dates where forest cover has been impacted greatly by
humans compared to the ecological potential for trees to grow, then
earlier dates should be encouraged. For others, later dates may be
suitable or all that is practical. Each country should then report on
whether the loss of forest cover, if any, is causing or is suspected of
causing environmental or social problems: soil erosion, degradation of
water quality or supply, loss of forest products such as fire wood,
timber, non-wood products. Each should indicate whether corrective
action is in place, wanted, possible or not needed, wanted etc. This
action/report allows each country to indicate whether they consider
themselves for be an LFC for the purposes of the definition.
- A final possibility "forward looking" of
changes to forest cover. If we set a benchmark with our definitions as
on/about the year 2000 (which the TBFRA and the Global Forest Resource
Assessment are trying to do) we can then look out in the future instead of
concentrating attention on what has happened in the past centuries.
Realistically speaking the best that can be done at present for all
countries is to present the situation now; derive some arbitrary measures
of what is meant by low forest cover; then monitor/repeat the exercise in
10,20, ..., 100 years time to quantify what is changing. We would
have to hold the definitions constant for a reasonable period of time -
such as has been agreed in the FAO definitions for the year 2000
assessment. Measures based on history are always going to be subject to a
raft of reasons for wanting to use different dates. If we set the
benchmark now so that we look ahead we avoid this potentially political problem.
Other definitions could be
written to distinguish how much of the forest is officially protected vs. the
amount of forest that exists, but is not protected and may therefore be subject
to change.
The "historical vs.
actual forest cover" is a useful indicator if the main purpose of the
exercise is to show what portion of a country's "original" forest
resource base remains today. The further back in time one goes to define
"historical" cover, the closer the indicator comes to being a measure
of "potential" cover (i.e., that amount of forest cover that would
exist in the absence of human activity, given the ecological/climatic
characteristics of the region.).
3.1 Thresholds: For specifying a thresholds here
are a couple of options:
- Use island biogeography could provide one perspective
from a biodiversity standpoint. Lose XX and you lose YY percent of your
species. (what is it...90% forest loss means eventual loss of 50% of
forest-associated species?) Finally, these cutoffs and distinctions should
be made by forest types as well as by country.
- Apply an arbitrary threshold. For example, low forest
cover would apply only where the people had disrupted say more than 80% of
whatever amount of forest the country started with millennia ago. The view
that ~80% could still convert back to forests might be theoretically
possible if the population, developed areas and agriculture were all
removed, but it would seem better to express the point in terms of
original cover.
- Some countries will have low acreages but the maximum
possible in forest. To bulk them as low-forest seems less reasonable,
unless it is done just for quantitative purposes. If a country has less
than 10% of its potential forest then it seems appropriate to call it a
'low forest country'. Keep it simple would suggest a pure quantitative
approach (% of all land, 5% seems a number that would truly suggest a
minimum role of forestry and forests for the country)
It is not the absolute
forest cover, or the absolute proportion lost of forests that are most
important, but whether what was lost is causing problems. If only 25% is 'gone'
and it comes mostly from steep land in water catchments, then it can be very
serious for land managers. If forest loss is 70% and comes from flat land
now under stable agriculture and the country wants agriculture, not forestry,
should anyone seriously complain? Some countries are small and occupy
only part of one or a few biozones whereas other countries are vast and cover
many biomes. These differences are often reflected in how countries
respond to land use changes. 10K ha of forest lost in one country could
be devastating, but scarcely noticeable in another. Absolute levels of
loss by country are not necessarily useful. Remember that country
boundaries have only a little to do with how variation in the natural world is
distributed.
3.2 Example: Table 4 is an example listing of
countries with less than 10 percent of their original forest land remaining.
Data are extracted from Appendix 1.
|
Table 4 - Listing of Countries having less than 10 percent
of their Original Forest remaining |
|
|
Country |
Forest/ Original Forest % |
|
Barbados |
0.00 |
|
Cayman Islands |
0.00 |
|
French Polynesia |
0.00 |
|
Malta |
0.00 |
|
Netherlands Antilles |
0.00 |
|
Yemen |
0.07 |
|
Lesotho |
0.27 |
|
Haiti |
0.77 |
|
Iceland |
0.81 |
|
Mauritania |
3.18 |
|
Egypt |
3.34 |
|
Jordan |
3.90 |
|
Israel |
4.22 |
|
Somalia |
4.64 |
|
Saudi Arabia |
4.68 |
|
Pakistan |
4.87 |
|
Eritrea |
4.97 |
|
Algeria |
5.04 |
|
El Salvador |
5.08 |
|
Comoros |
5.59 |
|
Syrian Arab Republic |
6.20 |
|
Tunisia |
6.50 |
|
Lebanon |
6.54 |
|
Singapore |
6.67 |
|
Bangladesh |
7.40 |
|
Niger |
7.62 |
|
St. Lucia |
8.20 |
|
Swaziland |
8.43 |
|
Gambia |
8.56 |
|
Kenya |
9.50 |
|
Ireland |
9.69 |
3.3 Implications: The implication is obvious. In theory, countries that
previously had forest area have the possibility to become reforested. This
could lead to donor assistance for reforestation projects.
An obvious disadvantage is
that the historic or "natural" land capability may be highly
speculative in degraded areas and countries with a long history of human
influence. In addition, the ratio actual/potential may be too
controversial with all the moral baggage about what the forest area
"should" be.
A problem with relying solely
on "past vs. present" comparisons is that the longer the timeframe
becomes, the more difficult it is to distinguish historical forest loss from
contemporary loss. Egypt and El Salvador, for example, have both experienced
severe deforestation, but at very different points in time. If part of our
purpose were to identify those countries where current forest pressure
(for lack of a better term) is greatest, how would this ratio provide that
information? The goal should be to use past data to help us identify current
priorities so that we can have a positive impact on the future of forests.
4. Combinations: A first filter could distinguish
between countries that have large potential and limited potential for
increasing their cover through re/afforestation. A second (per capita forest
cover) could identify those countries where the forest resource base is under
the greatest strain from current demographic pressure (and thus are a high
priority for development assistance either in the form of forestry/natural
resource management and/or family planning & general education &
development aid).
Using a per capita
indicator (in combination with other variable like income, climate, etc.) would
be big step forward in highlighting those countries/regions where population
programs could play a major role in the long-term success of sustainable
forestry initiatives. It would also draw attention to the enormous pressure of
agricultural production on forests in high population areas and help poke some
holes in the "it's all about logging" argument.
We considered a use of all
three approaches on a 3-dimensional plot and discuss the implications of different
directions of movement within that space. For example, a country which has
little forest as % land area AND as %original has more options for adding to
forest resources, while one that has a small amount of forest as % land area,
which is nearly as much as it ever was has fewer options, but possibly still
more than if in the same position on those two axes it also had a very low
forest per capita.
4.1 Thresholds: A threshold should based on
regional forest conditions (ecoregions perhaps?) while adjusting the threshold
further to take into account the country's population (this second threshold
option should allow some equity between countries by incorporating concerns
over differing populations) to determine if a country should be classified as
low forest cover. Any compromise requires a "weighting" of the
factors and it is not always easy to get international agreement on what these
should be because inevitably political considerations arise. Whatever is
finally decided upon is quite clearly spelt out in any reports, etc., which are
produced. International comparisons are difficult beasts at the best of
times and forestry ones are even more difficult to make sense of because of the
considerable variances which exist in "original forest cover" and the
histories of human settlement, population densities, etc. It is not the numbers
(however derived) that really matter. We will find "clusters of
countries" with the numerical values around about the same levels with,
possibly, nothing much between the clusters, rather than a continuum in the
values. Reporting this internationally needs to draw attention to a whole
range of differences in history, climate, soils, etc. It will be the
differences that are important as these will illustrate the complexities of
trying to capture simply what is meant by "low forest cover" in a
global context.
4.2 Example: As an example of a combination, we
did a sort of Appendix 1 using the following sequence - first, all countries
having less than 10 % FOWL cover. This gives us an indication of countries with
LFC based on FOWL cover only. Next we sorted these countries to see which had
less than 10 percent of their remaining forestland. Finally we sorted those
remaining countries that had less than 0.73 FOWL per capita. This gave us an
indication of where forest resources are scarce due to land conversion and
where demand would be high. The countries we found included Algeria, Egypt,
Eritrea, Haiti, Iceland, Ireland, Israel, Jordan, Lesotho, Malta, Netherlands
Antilles, Pakistan, Saudi Arabia, Seychelles, Singapore, Swaziland, Syrian Arab
Republic, Tajikistan, Tunisia, United Arab Emirates, Uruguay, and Yemen.
A combination of thresholds
may be used. Figure 5 shows the 26 countries (shaded) having both less than 10%
of the original forestland left and less than 0.73 FOWL/capita.
4.3 Implications: A combination definition,
such as the one illustrated above, provides the kind of information one needs
to know where lands can be reforested as well as where the high demands for
forest goods and services may be (see Appendix 2).
Using a single indicator is
attractive because it is relatively simple and easy to explain. However, using
a single indicator—whatever it may be—often leaves out crucial considerations.
Admittedly, forest cover per capita is an example of this problem, as it does
not capture the difference between the suitability of different regions for
supporting large areas of forest cover (e.g., Iceland vs. Indonesia. "Low
forest cover" concept should incorporate two or more indicators. For
example, one could use the "historic vs. current" or "potential
vs. actual" forest cover ratio to separate countries based on how much of
their forest resource base has been preserved or at least reclaimed. (A key
benefit of this ratio is that it avoids the pitfalls of using "forest as a
% of land area" that have already been discussed in relation to Australia
and Namibia.) However, this ratio alone does not adequately identify countries
in which current demands on forests are greatest. Thus, using the per capita
indicator in combination with the "potential to actual" ratio would
help further determine where population dynamics are exerting pressure on the
forest resource base.
The usefulness of a two or
three tiered system (that includes population as one of the indicators) is that
it allows one to make two levels of distinctions between forest cover in
different countries—the first "cut" based on the amount of historical
forest loss, and the final cut based on the relative pressure being placed on
the forest resource today.
OTHER CONSIDERATIONS
- A couple reviewers suggested that we need to not only
look at national totals and averages in identifying countries with LFC,
but we also have to consider large LFC areas within countries. This
certainly would increase the number of countries that could be eligible
for funding assistance. Figure 6 shows tree cover density for the
contiguous United States. The gray areas are areas with less than 10% tree
cover. Those in the eastern U.S. were once forested and would come back as
forest if left alone. Those in Great Plains and intermountain regions
could only be afforested with special effort.
The
point is that all countries have some areas of Low Forest Cover. Some due to
land conversion, others due to ecological and environmental factors. Even
though the US does not qualify as a LFC country by the above definitions, it
does have vast areas, larger than many countries of the world, which would
qualify as having LFC.
- A second point raise was to separate those LFC
countries into two categories - those that are island nations and those
that are dry regions. This certainly could be done
KEY ISSUES
In order to determine what
definition to use and thresholds to use, there are some key issues that the IFF
needs to address.
- What is the purpose of identifying LFC countries -
increase forest area or tree covered area, decrease population and
consumption, equalize available resources among nations? If the goals are
economic or environmental (carbon sequestration, soil and water
protection) then the establishment of plantation forests may suffice. If
the goal is ecological, then natural regeneration through site protection
may be the appropriate course.
- Definition of forestland - National definitions of
forestland vary considerably (Lund 2000). What may be considered
forestland by one nation, may not be so considered by another. National
definitions take on one or all of the following forms - an administrative
unit, a descriptor of land use, a descriptor of land cover, or a
combination. The difference between land use and land cover is that under
a land use definition, a piece of land with out trees (such as a clearcut)
may be called forestland. Under land cover this would not. Similarly under
a land use definition, an area can be covered with trees and not
considered forestland such as an olive grove. Under a land cover
definition, agricultural plantations may be considered forestland.
Here
we are speaking of forest cover - so we can rule out administrative units and
land use. But are we concerned about all tree cover - which would include permanent
crop plantations (oil palm, rubber trees, nut and fruit trees, etc) as will as
trees off forest, bamboo stands, and "traditional" forestland.
A
good working land cover definition would include thresholds specifying a
minimum size area, minimum percent cover minimum tree height, and minimum strip
width as well as exclusions. Again national definitions of forest cover vary
and very few countries have specified thresholds. Figure 7, for example, shows
tree height thresholds used in national definitions of forestland. Note that
Kenya has a minimum tree height of 2 meters and Sudan of 10 meters. Assuming
all other things being equal, Kenya would have more forestland than Sudan
because Kenya would include lands with shorter trees. By raising the threshold,
a country could claim less forestland.
For
these reasons, some type of international definition of is desired. This has
problems, however, as nations may not have data on hand to re-compute their
forestland area to the international definition. Using figure 7 as an example,
a reasonable international threshold for tree heights may be 5 m. This is the
standard used for the UN/ECE/FAO Global Forest Resource Assessment 2000 (FRA
2000) shown in black. Since countries like Sudan use a taller minimum tree
height in classifying their forestland, they may not have data on hand to
re-compute area based on a lower threshold. The lands with shorter trees may
not have been considered forestland and therefore may not have been included in
Sudan's national inventories.
Figure
8 shows similar national thresholds for minimum percent tree cover. Threshold
crown cover varies from 1 percent for Iran to 80 percent for Zimbabwe. FRA 2000
is 10 percent. All things being equal, countries with larger thresholds will
appear to have less forestland than those with smaller thresholds. As with tree
heights, converting national estimates to an international standard may prove
difficult for those countries that have thresholds greater than the
international standard.
Finally,
in shifting to an international standard, some countries may appear to lose
forestland while others will appear to gain when compared to national
estimates.
- This brings up the third problem of data availability.
Where will the data come from once the LFC definition is established? Will
it come from national statistics, international sources?
- Finally, who will do the monitoring to ensure
legitimate changes are being made?
DISCUSSION
We need answers to the
following questions:
- What does the IFF want to happen as a result of the
selected definition?
- What definitions to use?
- What data are available?
- Where will new data come from?
- Who will oversee or monitor the results?
The use of the term
"forest" here could mean forestland (however defined) or tree covered
lands (treeland) depending on the objectives of IFF. Forestland could include
or exclude agricultural plantations depending on how forestland is defined.
Treelands, on the other hand, would include all lands with trees on them
meeting minimum threshold requirements regardless of land use. A Forestland
approach would be desirable if the concern is primarily ecological. A treeland
approach is useful for economic and environmental objectives. Treeland area
estimates can be obtained from remote sensing. Forestland estimates may require
ground truth as well.
Intuitively, as a minimum,
IFF should use the ratio of current "forest" to original forest
cover. A list of countries having the lowest ratio could be generated. This
list could be prioritized by sorting on those countries which have the least
forest/capita.
A population-based ratio is
an informative indicator for development agencies to use in making resource
allocation determinations. The dominant historical relationship between people
and forests has been that as the former advances the latter retreats. If, as
the saying goes, the past is prologue, then population dynamics will remain a
key factor—though certainly not the only factor—demanding consideration by all
parties interested in achieving "sustainable" resource management.
Basing a working definition
of LFC on combinations of indicators is attractive in that is possibly allows
for a "richer" interpretation of the difficulties to emerge in the
political discussion which IFF will have. Dennis' work with the thresholds
suggested in the paper (Appendix 2) has perhaps brought in a few other
countries but again, with the exception of Netherlands, they are generally the
countries we would have expected to see. Using slightly higher thresholds to
bring in a couple of "developed" countries may help the process. More
work could obviously be done on this.
We need to keep in mind
that the nature of the raw data may be inaccurate and so a ratio of inaccurate
figures would be even worse. It is important to quote all three pieces of
information pertaining to the nation or region in question, i.e. total forest
and land areas, and total population, but add to those, further data on the
date to which these figures refer and some indication of the precision and
accuracy of these estimates together with annual or periodic rates of change in
forest and land areas and population. If nothing else this will force analysts
to review the quality of the information they are quite content to convert into
ratios. Any composite index should reflect the nominal error levels and allow
sensitivities to guide categorization. Emphasize getting good basic data on
areas and populations before trying to derive simplistic indices.
Data availability and
source are also considerations. The LFC definition has to be based upon data
that are available or are easily obtainable. If IFF wants within country
breakdowns, data must be also spatially registered. This means that maps -
vegetation cover, demographics must be available for each country.
The data used in Appendix 1
of this report came from FAO, UNECE, WCMC and WRI. The forest and FOWL
estimates are based upon land use. The UN data are obtained from a variety of
sources harmonized to a common definition and point in time. They are not
spatially registered. The estimates include areas that may be currently devoid of
trees but are expected to be reforested in the future. They may include rubber
plantations and exclude other types of tree crops.
Current forestland or
treeland cover estimates can be improved by using remote sensing and one data
source. NASA and the University of Maryland (UM) have created such a database
for the globe. See http://glcf.umiacs.umd.edu. It is our understanding that the
developers are working towards refining the mapping. Country estimates of treeland
may be obtained by superimposing national boundaries on the NASA/UM map.
The Original Forest
estimates are based upon ecological maps depicting what areas may have been
forested 8000 years ago. While, no one knows for sure what the forest cover was
8000 years ago, this is the only global database we have available and it is
spatially registered (see http://www.wri.org/ffi/maps/ ). It can also be used as a caveat
for "original treeland."
RECOMMENDATIONS
- Determine what it is that IFF wants to happen if funds
are given to countries of LFC - expand forest cover or expand tree cover.
This will help to determine what lands to include and what
"forest" definition to use.
- Determine what thresholds to use for determining if
countries are in or out. The thresholds may be arbitrary based upon funds
available or "scientifically" based.
- Determine who will monitor if objectives are being met
and how the monitoring will be done. The monitoring aspect can also have a
bearing on the definition decided upon in recommendation 1. It is easier
to monitor "tree" cover than it is to monitor "forest"
cover.
- As to LFC areas within country, all countries have such
land. Consider leaving funding of restoring such areas up to the individual
countries.
ACKNOWLEDGEMENTS
We thank the following
people for their input to this paper:
Ananin, Nick
Barton, James P
Beckett, Doug
Botero, L.S.
Bradley, Roger
Bryant, Dirk
Cihlar, Josef
Delaney, Jeff
Dennis, John
Dennis, Judith
Ellis, Liz
Gardner-Outlaw, Tom
Gillam, Simon
Glen, William
Gonzalez, Patricio
Hnatiuk, Roger
Jensen, J
Joshi, Mahendra
Kapos, Val
Korotkov, Alexander
Lamers, Sjef
Magnussen, Steen
Marten, K.D.
Mehmood, Sayeed
Melnyk, Mary
Michaelson, Tage
Mize, Carl W.
Niemann, Tom
Norton, Douglas
Null, Bill
Palo, Matti
Persson, Reidar
Plum, Peter Monk
Prins, Christopher
Prüller, Renate
Sampson, N.
Schmitz, Friedrich
Schmutzenhofer, Heinrich
Steffenson, John
Taal, Bai-Mass
Vanclay, Jerry
Whyte, Graham
Wong, Nelson
As well as the participants
from the International Meeting of Experts on Special Needs and Requirements of
Developing Countries with Low Forest Cover and Unique Types held 4-8 October
1999 in Tehran, Iran. Countries participating included: Armenia, Azerbaijan,
Bangladesh, Canada, Cyprus, Denmark, Egypt, Ethiopia, Finland, France, Germany,
Ghana, Greece, India, Iran, Iraq, Jordan, Kazakhstan, Kenya, Lebanon, Libya,
Mali, Niger, Nigeria, Oman, Pakistan, Portugal, Russia, Senegal, South Africa,
Sudan, Syria, Tajikistan, Tunisia, Turkey, Turkmenistan, and Yemen. Lastly
thanks are given to the participants from the Side Event at the IFF4 meeting in
New York City, 2 February 2000.
A special thanks to:
- Risto Päivinen (risto.paivinen@efi.fi) for offering the services of
IUFRO Research Group 4.02 to help with the report,
- Brian Haddon (B.Haddon@NRCan.gc.ca) and Michele Kaennel
(kaennel@wsl.ch) for setting up the IUFRO Working Party 6.03.02 LFC
discussion list,
- Val Kapos (WCMC), Dirk Bryant (WRI), and Alex Korotkov
(UNECE) for sharing their data, and
- Judith Dennis and James Barton (New Zealand Ministry of
Agriculture and Forestry) for the multivariate analyses (Appendix 2) of
the data.
REFERENCES
Anon. 1999. Proceeding: The
International Meeting on Special Needs and Requirements of Developing Countries
with Low Forest Cover and Unique Types of Forests. Tehran, Islamic Republic of
Iran. 4-8 October 1999. 190 p.
DRAFT - THE NEEDS AND
REQUIREMENTS OF COUNTRIES WITH LOW FOREST COVER Prepared for United Nations
Commission on Sustainable Development Intergovernmental Panel on Forests by
WCMC (Val Kapos valk@wcmc.org.uk)
E/CN.17/IPF/1996/18 9
August 1996 COMMISSION ON SUSTAINABLE DEVELOPMENT, Ad Hoc
Intergovernmental Panel on Forests, Third Session. 8-20 September 1996,
IMPLEMENTATION OF UNITED NATIONS CONFERENCE ON ENVIRONMENT AND DEVELOPMENT
DECISIONS RELATED TO FORESTS AT THE NATIONAL AND INTERNATIONAL LEVEL, INCLUDING
AN EXAMINATION OF SECTORAL AND CROSS-SECTORAL LINKAGES. Programme element
I.5: Needs and requirements of countrieswith low forest cover. Report of
the Secretary-General (Tom Gardner-Outlaw <tgo@popact.org).
INTERAGENCY PARTNERSHIP ON
FORESTS: Implementation of IPF Proposals for Action by the TFF INTERAGENCY TASK
FORCE ON FORESTS (ITFF) June 1997 (Tom Gardner-Outlaw <tgo@popact.org).
Iremonger, Susan. 1998.
Report to accompany maps and statistics for the World Commission for Forests
and Sustainable Development. Cambridge, UK: World Conservation Monitoring
Centre. 5 p.
Lund, H. Gyde. 1998. A
Comparison of Multipurpose Resource Inventories (MRIs) Throughout the World.
Working Paper 14. Joensuu, Finland: European Forest Institute. 46 p.
Lund, H. Gyde. 2000.
Definitions of forest, afforestation, deforestation and reforestation.
Unpublished report. http://home.comcast.net/~gyde/DEFpaper.html Gainesville, VA: Forest Information
Services. Misc. pagination.
Lund, H. Gyde; Iremonger,
Susan. 1998. Omissions, commissions,
and decisions - the need for integrated resource assessments.In: Proceedings First International
Conference on Geospatial Information in Agriculture and Forestry. Decision
Support, Technology, and Applications. 1-3 June 1998. Lake Buena Vista,
FL. Ann Arbor, MI: ERIM International, Inc. Volume I: 182-189.
WCMC. 1998. Source
documentation for the Original Forest Cover map compiled for the WCFSD.
Cambridge, UK: World Conservation Monitoring Centre. 11 p.
UN-ECE/FAO. 1997.
UN-ECE/FAO Temperate and Boreal Forest Resources Assessment 2000 - Terms and
Definitions. GE. 97-22231. Geneva. 13 p.
APPENDIX 1 - BASIC DATA FOR LOW FOREST COVER ANALYSIS
Included in this Appendix
is a matrix using the best available global data on land area, Forest and Other
Wooded Lands and Original forest area where:
Forest
Land - Land with
tree crown cover (or equivalent stocking level) of more than 10 percent and
area of more than 0.5 ha. The trees should be able to reach a minimum height of
5 m at maturity in situ. May consist either of closed forest formations where
trees of various storeys and undergrowth cover a high portion of the ground; or
of open forest formations with a continuous vegetation cover in which tree
cover exceeds 10 percent. Young natural stands and all plantations established
for forestry purposes which have yet to reach a crown density of 10 percent or
tree height of 5 m are included under forest, as are temporarily unstocked as a
result of human intervention or natural causes but which are expected to revert
to forest. Includes: Forest nurseries and seed orchards that constitute an
integral part of the forest; forest roads, cleared tracts, firebreaks, and
other small open areas within the forest; forest in national parks, nature
reserves and other protected areas such as those of special environmental,
scientific, historical, cultural, or spiritual interest; windbreaks and
shetlterbelts of trees with an area of more than 0.5 ha and a width of more
than 20 m. Rubberwood plantations and cork oak stands are included. Excludes:
Land predominantly used for agricultural practices (UN-ECE/FAO 1997).
Other Wooded Land - Land either with a tree crown cover (or equivalent
stocking level) of 5-10 percent of trees able to reach a height of 5 m at
maturity in situ; or a crown cover (or equivalent stocking level) of more than
10 percent of trees not able to reach a height of 5 m at maturity in situ (e.g.
dwarf or stunted trees) and shrub or bush cover. Excludes: Areas having the
tree, shrub or bush cover specified above but of less than 0.5 ha and width of
20 m, which are classed under "other land"; Land predominately used
for agricultural practices (UN-ECE 1997).
Original
Forest Land - That
estimated to have covered the planet about 8,000 years ago, before large-scale
disturbance by modern society began. (http://www.wri.org/ffi/lff-eng/)
The reader is cautioned in
using this information. The table should not be used beyond an example until
its contents are verified by the primary sources and data providers. In
particular the Original Forest estimates and the Forest Land estimates for Kuwait,
Mauritius, Saint Helena, Suriname, Turkmenistan, and Uruguay need to be
verified in addition to the population estimates for Macedonia. Also not listed
are countries that have been void of forests for some time including Oman,
Qatar, etc.
|
Country |
Population (1000) |
Total Area (1000 ha) |
FOWL (1000 ha) |
Forestland (1000 ha) |
FOWL/ Total Area % |
Forest Land/ Total Area % |
FOWL/ Capita |
Original Forest (1000 ha) |
Forest/ Original Forest % |
|
Afghanistan |
21354 |
65209 |
2614 |
1398 |
4.01 |
2.14 |
0.122 |
2679 |
52.18 |
|
Albania |
3119 |
2729 |
1048 |
1030 |
38.40 |
37.74 |
0.336 |
2863 |
35.98 |
|
Algeria |
30081 |
238174 |
3945 |
1861 |
1.66 |
0.78 |
0.131 |
36943 |
5.04 |
|
Angola |
12092 |
124670 |
77198 |
22200 |
61.92 |
17.81 |
6.384 |
105994 |
20.94 |
|
Antigua and Barbuda |
67 |
44 |
26 |
9 |
59.09 |
20.45 |
0.388 |
27 |
33.33 |
|
Argentina |
36123 |
273669 |
50936 |
33942 |
18.61 |
12.40 |
1.410 |
109707 |
30.94 |
|
Armenia |
3536 |
2820 |
334 |
334 |
11.84 |
11.84 |
0.094 |
1209 |
27.63 |
|
Australia |
18520 |
764444 |
145613 |
40908 |
19.05 |
5.35 |
7.862 |
231470 |
17.67 |
|
Austria |
8140 |
8254 |
3924 |
3840 |
47.54 |
46.52 |
0.482 |
7928 |
48.44 |
|
Azerbaijan |
7669 |
8660 |
990 |
990 |
11.43 |
11.43 |
0.129 |
2981 |
33.21 |
|
Bahamas |
296 |
1001 |
186 |
158 |
18.58 |
15.78 |
0.628 |
1363 |
11.59 |
|
Bangladesh |
124774 |
13017 |
1472 |
1010 |
11.31 |
7.76 |
0.012 |
13648 |
7.40 |
|
Barbados |
268 |
43 |
5 |
0 |
11.63 |
0.00 |
0.019 |
14 |
0.00 |
|
Belarus |
10315 |
20700 |
8936 |
7865 |
43.17 |
38.00 |
0.866 |
19930 |
39.46 |
|
Belgium |
10141 |
3025 |
672 |
646 |
22.21 |
21.36 |
0.066 |
2904 |
22.25 |
|
Belize |
230 |
2280 |
2117 |
1962 |
92.85 |
86.05 |
9.204 |
2240 |
87.59 |
|
Benin |
5781 |
11262 |
11497 |
4625 |
102.09 |
41.07 |
1.989 |
11591 |
39.90 |
|
Bhutan |
2004 |
4700 |
3168 |
2756 |
67.40 |
58.64 |
1.581 |
3204 |
86.02 |
|
Bolivia |
7957 |
108438 |
57977 |
48310 |
53.47 |
44.55 |
7.286 |
76979 |
62.76 |
|
Bosnia and Herzeovina |
3675 |
5100 |
2710 |
2710 |
53.14 |
53.14 |
0.737 |
5173 |
52.39 |
|
Botswana |
1570 |
56673 |
26561 |
13917 |
46.87 |
24.56 |
16.918 |
30404 |
45.77 |
|
Brazil |
165851 |
845651 |
671921 |
551139 |
79.46 |
65.17 |
4.051 |
764739 |
72.07 |
|
British Virgin Islands |
20 |
15 |
5 |
4 |
33.33 |
26.67 |
0.250 |
12 |
33.33 |
|
Brunei Darussalam |
315 |
527 |
458 |
434 |
86.91 |
82.35 |
1.454 |
594 |
73.06 |
|
Bulgaria |
8336 |
11019 |
3903 |
3590 |
35.42 |
32.58 |
0.468 |
10776 |
33.31 |
|
Burkina Faso |
11305 |
27380 |
13813 |
4271 |
50.45 |
15.60 |
1.222 |
4436 |
96.28 |
|
Burundi |
6457 |
2565 |
1314 |
317 |
51.23 |
12.36 |
0.204 |
1571 |
20.18 |
|
Cambodia |
10716 |
17652 |
13724 |
9830 |
77.75 |
55.69 |
1.281 |
17713 |
55.50 |
|
Cameroon |
14305 |
46540 |
35905 |
19598 |
77.15 |
42.11 |
2.510 |
46771 |
41.90 |
|
Canada |
30563 |
915912 |
453300 |
244571 |
49.49 |
26.70 |
14.832 |
639148 |
38.27 |
|
Cayman Islands |
36 |
26 |
7 |
0 |
26.92 |
0.00 |
0.194 |
28 |
0.00 |
|
Central African
Republic |
3485 |
62298 |
46754 |
29300 |
75.05 |
47.03 |
13.416 |
62287 |
47.04 |
|
Chad |
7270 |
125920 |
32450 |
11025 |
25.77 |
8.76 |
4.464 |
52916 |
20.83 |
|
Chile |
14824 |
74880 |
16583 |
7892 |
22.15 |
10.54 |
1.119 |
34727 |
22.73 |
|
China (including
Taiwan) |
1255698 |
932641 |
162029 |
133323 |
17.37 |
14.30 |
0.129 |
571664 |
23.32 |
|
Colombia |
40803 |
103870 |
63231 |
52988 |
60.88 |
51.01 |
1.550 |
105629 |
50.16 |
|
Comoros |
658 |
223 |
41 |
9 |
18.39 |
4.04 |
0.062 |
161 |
5.59 |
|
Congo |
2785 |
34150 |
25285 |
19537 |
74.04 |
57.21 |
9.079 |
34304 |
56.95 |
|
Costa Rica |
3841 |
5106 |
1569 |
1248 |
30.73 |
24.44 |
0.408 |
5125 |
24.35 |
|
Croatia |
4481 |
5598 |
2105 |
1775 |
37.60 |
31.71 |
0.470 |
5526 |
32.12 |
|
Cuba |
11116 |
10982 |
3262 |
1842 |
29.70 |
16.77 |
0.293 |
10969 |
16.79 |
|
Cyprus |
771 |
924 |
280 |
140 |
30.30 |
15.15 |
0.363 |
1017 |
13.77 |
|
Czech Republic |
10282 |
7735 |
2630 |
2630 |
34.00 |
34.00 |
0.256 |
7860 |
33.46 |
|
Côte d'Ivoire |
14292 |
31800 |
18952 |
5469 |
59.60 |
17.20 |
1.326 |
31992 |
17.09 |
|
Dem. Republic of the
Congo (Zaire) |
49139 |
226760 |
166076 |
109245 |
73.24 |
48.18 |
3.380 |
227911 |
47.93 |
|
Denmark |
5270 |
4253 |
538 |
445 |
12.65 |
10.46 |
0.102 |
4342 |
10.25 |
|
Djibouti |
623 |
2318 |
1320 |
22 |
56.95 |
0.95 |
2.119 |
81 |
27.16 |
|
Dominica |
71 |
75 |
50 |
46 |
66.67 |
61.33 |
0.704 |
61 |
75.41 |
|
Dominican Republic |
8232 |
4838 |
1582 |
1582 |
32.70 |
32.70 |
0.192 |
4826 |
32.78 |
|
Ecuador |
12175 |
27684 |
15576 |
11137 |
56.26 |
40.23 |
1.279 |
22222 |
50.12 |
|
Egypt |
65978 |
99545 |
34 |
34 |
0.03 |
0.03 |
0.001 |
1018 |
3.34 |
|
El Salvador |
6032 |
2072 |
890 |
105 |
42.95 |
5.07 |
0.148 |
2066 |
5.08 |
|
Equatorial Guinea |
431 |
2805 |
2719 |
1781 |
96.93 |
63.49 |
6.309 |
2535 |
70.26 |
|
Eritrea |
3577 |
10100 |
282 |
282 |
2.79 |
2.79 |
0.079 |
5677 |
4.97 |
|
Estonia |
1429 |
4227 |
2011 |
2011 |
47.58 |
47.58 |
1.407 |
4249 |
47.33 |
|
Ethiopia |
59649 |
100000 |
41991 |
13579 |
41.99 |
13.58 |
0.704 |
56950 |
23.84 |
|
Fiji |
796 |
1827 |
859 |
835 |
47.02 |
45.70 |
1.079 |
2345 |
35.61 |
|
Finland |
5154 |
30462 |
22605 |
21720 |
74.21 |
71.30 |
4.386 |
30546 |
71.11 |
|
France |
58683 |
54325 |
16989 |
15156 |
31.27 |
27.90 |
0.290 |
53785 |
28.18 |
|
French Guyana |
167 |
8815 |
8318 |
7990 |
94.36 |
90.64 |
49.808 |
8370 |
95.46 |
|
French Polynesia |
227 |
366 |
115 |
0 |
31.42 |
0.00 |
0.507 |
18 |
0.00 |
|
Gabon |
1167 |
25767 |
19966 |
17859 |
77.49 |
69.31 |
17.109 |
26511 |
67.36 |
|
Gambia |
1229 |
1000 |
286 |
98 |
28.60 |
9.80 |
0.233 |
1145 |
8.56 |
|
Georgia |
5059 |
6970 |
2988 |
2988 |
42.87 |
42.87 |
0.591 |
5344 |
55.91 |
|
Germany |
82133 |
34934 |
10740 |
10740 |
30.74 |
30.74 |
0.131 |
34961 |
30.72 |
|
Ghana |
19162 |
23002 |
18013 |
9022 |
78.31 |
39.22 |
0.940 |
23957 |
37.66 |
|
Greece |
10600 |
12926 |
6513 |
3359 |
50.39 |
25.99 |
0.614 |
13253 |
25.35 |
|
Grenada |
93 |
34 |
11 |
4 |
32.35 |
11.76 |
0.118 |
31 |
12.90 |
|
Guadeloupe |
443 |
169 |
93 |
80 |
55.03 |
47.34 |
0.210 |
117 |
68.38 |
|
Guatemala |
10801 |
10843 |
9465 |
3841 |
87.29 |
35.42 |
0.876 |
10777 |
35.64 |
|
Guinea |
7337 |
24586 |
17484 |
6367 |
71.11 |
25.90 |
2.383 |
24562 |
25.92 |
|
Guinea-Bissau |
1161 |
2812 |
2309 |
2309 |
82.11 |
82.11 |
1.989 |
3455 |
66.83 |
|
Guyana |
850 |
19685 |
18755 |
18577 |
95.28 |
94.37 |
22.065 |
20058 |
92.62 |
|
Haiti |
7952 |
2756 |
139 |
21 |
5.04 |
0.76 |
0.017 |
2711 |
0.77 |
|
Honduras |
6147 |
11189 |
6054 |
4115 |
54.11 |
36.78 |
0.985 |
11351 |
36.25 |
|
Hungary |
10116 |
9213 |
1811 |
1811 |
19.66 |
19.66 |
0.179 |
6985 |
25.93 |
|
Iceland |
276 |
8844 |
130 |
30 |
1.47 |
0.34 |
0.471 |
3686 |
0.81 |
|
India |
982223 |
297319 |
82648 |
65005 |
27.80 |
21.86 |
0.084 |
236396 |
27.50 |
|
Indonesia |
206338 |
181157 |
145108 |
109791 |
80.10 |
60.61 |
0.703 |
189631 |
57.90 |
|
Iran |
65758 |
163600 |
11437 |
1544 |
6.99 |
0.94 |
0.174 |
3221 |
47.94 |
|
Iraq |
21800 |
43737 |
192 |
83 |
0.44 |
0.19 |
0.009 |
376 |
22.07 |
|
Ireland |
3681 |
6890 |
591 |
591 |
8.58 |
8.58 |
0.161 |
6097 |
9.69 |
|
Israel |
5984 |