Post on 13-Jul-2020
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I ,
:: ~ ___ ,~_:~I~J:~:~CC~ ANALYSIS FOil. DECISION MAKING IN
NATURAL RESOBReE lIANAGEMENT FOR
SDSTAINABLE AGRICULTBRE
PHASE 1 AESU
ENVIRONMENTAL DESCRIPTION AND CLASSIFICATION
INTERlIISSION • EeONOllISTS
SENSITIVITY ANALYSIS OF CRITERIA
FOR GROllIR. EQUITY AHD SUSTAINABILITYc
CHOICE OF EH'IIONlIENTAL eLASSES,
PRASE TI AESU
eHARACTERISA TION OF tAND USE PATTERNS
IIITRIN ENVIRONlIENTAL CLASS
CONeLUSION • 1I0RKING G¡¡OUP 4
SELEeTION OF AGROECOSYSTElI i"''''--"'
, , .• t e' t
DATA ANALYSIS FOR DECISION KAKING IN NATURAL RESO!lRCE IlANAGEKENT
FOR SUSTAINAllLE AGRlCULTURE
PllASE 1.
7 Hay 1990 ,
P-," Jones & D~' Robison
Agroecological Studies Unit~CIAT
INTROOUCTIO!!
!he literature abounds with supposed definitions of sustainable
agricultura. Many of tuese tend te confusa the topie. Added te this
confusion is the fact that CIAr aparates in a ~ide range of
environments, both physical snd social. lt ls felt that Natural Resource
management researc.h 15 more sita specific thao germplasm improvement. It
was: cherefore necessaJ:y to hava a clear idea of che envirorunents of
possible areas of intervention.
Tha Agroecological Studies Unit (AEU) has been given t:he
responsibility of providing, mapping and analysing data on the
environment:s, demography and infrastructure of Latin America to assist
che CIAT managemenc in deciding on possible agroecological regions in
which to mQunC Natural Resource Mánagement (NRM) projects,
2
This effort was origina:'ly planned fer a time frame oi about 2
years, hQwever. exigencias of strategic planning have considerably
shortened this proces$, !he work was replanned into 2 phases, The firsc
of these has now come to fruition with this repor~, !he rationale behind
this division into phase 1 and Ir was to provide sufficient information
fer careful selection of a few Agroecological regions for further study
in depth in phase n. Phase 1 divided I...6tin America and the Caribbean
into broad environmental classes and characterised th~~e with the
available informa.cion to .assist in the decision process, 11:" has lasted
only sorne 2 mon~hs wi!:h various times out for heated discussion with
sorne of toe principals: in the proCess and wich some others not in the
process at a11! It drew on certain data froro the CIA! databases, a
cO!1siderab1e amO'.lnt of other data obtained .... ith the foresighe tnat chis
process might. occur sud finally with some very hard w-ork by a11 the
staff of AEU ta make up the difference.
3
METlIOD
DATA SOllRCES
!he land system database of CIAT contains much detallad information
on che lovland trapics of South America. Our brief in this phase ~as to
include a cross section oi a11 th~ environments snd social conditlons in
Latin Alnerica wbere CIAT might have a role. \Ve therefore opted for a
Phase 1 tabulation basad on more general data ta be consistent acroas
che continent. Ye decided ta use the Meegrid files develaped in CIAT by
the AEU, !hese files give the equivaLent of a paint quadrant picture oí
the continen~ at a resolution of 18.5 km. !bis resolution ls consistent
with che rural papulation 4nd level oi lnfrastructure data available in
the very short time of Phase 1. As with any paine quadrat study the
standard errors of che areas estimated are highly dependent on the
number of hits of che quadrat point. This technique 'should, ho .... ever.
give a suffici~nt idea of Che areas involved to al1ew the CIAT
management to proceed te a selection of (hopefully} less than 6
agroecological zones for further study in depth.
a- Ketgrid Files
The Metgrid files are an interpolation from the CIAr climate
database using as a g.rid basis the 10 minute grid oí the NOAA dig.ital
'Ierrain model and the central pixel from the UNEP/GEMS/GRID raster
version of the FAO 50i1 Map of the World. Hence the reference to a Point
Quadrat mentionad above.
Interpolation of climate data WaS done by weighted inverse sq~ared
distance from the nearest 4 stations in the database, correct:ed for
altltude 'Co che NOAA elevation using the standard tropical at:mosphere
lapse rate model cOlllmonly used by AEU. The spatial sprea.d o':: _ ..... ,na\..e
statioM is highly variable but tends to be more dense in areas were
there is a high variation in alt:itude and slope and where the majoricy
of thé population are often faund.
b ~ Legally Re~trict::ed Areas
Since Janua.ry 1989 ve have been gathering and digitizing the areas
in each country that are legally restricted from normal agricult~ra1
development. !hese for the most part are national parks, forest
reserves, indian reservations, ecological preserves or protected
catchrnent areas. Sooa countries report no such arcas and in others the
protection is ónly on papero However these areas represent a significant
proportion of out" target area and therefore we exc:luded them from Ol..lr
calculation of potential agricultural area of an environmantal class.
e - Populatlon
Both rural snd urban population are extremely unequally distributed
in Latin Americ.a, We include this information because we feel lt is
fundamental to know che Bize of the rural population in each
errvironmental class snd where the concentration 15. Most problems and
opportunities in agriculture are affected by population density,
5
As a firse approximátion \ole digitized a population map chat was
transposed from the Time Atlas population map. The actual population
represented by this map was c.aleulated by computer and a new map was
computar to represent 1986 rural population. n.e map
underestimated urban populatian so a correction factor Was applied by
country and Brazilian state so as to represent 1986 urban population on
a separate map.
This informativn was overlayed on che map of environmental classes
chus providing an estímate of rural and urban popula-:íon by
environmental class.
d- Access
Our brief was ta produce a realistic sse of enviror~ental classes
frem which ta choose. As che relative area of a class might be a
criteria for choosing between classes we feel the figure that should be
used 1s that area that 1s accessible witb current infrastructure. Our
ca1culation was te include all area within aach class that is within 30
km of either side of an a11 weather road, navigab1e river or sea coast.
S1nes January 1989 tbe Unit have been digitizing all~surface reads in
each country. For Brazil this meant d1g1tizing the entire 1989 rcad
Atlas, The 60 km corredor along eaeh road is a generous ast1mate
for the 1ncrease in aCcess that provides might occur over che next few
years, This analysis can be extended to fut.ure deve10pment 0=
1nfrastructure in more datailed studies.
6
For mese oi che SI chosen classes this exercise did not reduce
effective srsa muen. However for the humid forest classes it excluded
areas such as the Darían Straits, upper Río Negro snd mid Xingú ... hich
are truly inaccessible.
e~ Rural Income. per capita
As equ~ty 15 ene of the criceria for choosing research activities.
we included chis variable at the country sud Brazilia state levels. This
1s admittedly crude, but even wirhin Brazil the rural lncorna per capita
by stste variad froro around 150 $ (Maranhao and Pian!) to over, 2000 $
(Mato Grosso do Sul).
The data used lOas 1987 World Banks figures at che coun~ry leveL
Within Brazil we used figures in the 1980 ccnsus for gros s agricul:ural
produce per eapita by stste, che resulting differentials were applied co
che 1987 ~orld Bank figure for all of Brazil,
ENVlRONMENTAL CLASSIFICATION
The scope of Phase 1 of ~his project was vasto le included all of
Latin Amer1ca in which CIA! could support a reasonable role in ~~. This
forced us to certain assuroptions and/or criteria.
a- The environmental classification musc be simple enough to be
mappabla and not require unavailable data.
7
b~ lt muse be consistent with the data from which it 15 drawn.
c- le should reflee~ che environmental requirements of actual or
potential commodity crops tor a Cenere of Tropical Agricultura.
d- Environmental criteria should reflect the experience of scientist
working in the centre.
e- 10 reduce strain on che mind and on computing machinery, ridiculous
combinations should be rejected as SOon as possible,
Five environmel'lI::al criteria were decided upon basad on many years
of consultatión with CIAr commodity scientists.
1- $eason Length
This was calculated aS the nuntber of wet months where rainfall
exceeds 60% of potential evapotraospiration, caleulated by the methad of
Linaere (1978),
The classes were:
1 oVer 9 months wet
2 9 ta 1 months wet
3 6 ta 3 months wet
4 2 or les s . R€JECTED
8
NOTE:
Soma bea!1 areas are excluded by this rule. but no other CIAT erop can
manage the ~~~~~cy of class 4,
2, Temperature during the growing season.
Growing season ... as defined as that season with wet months (See 1
above) .
The classes were:
1.
2.
3.
4.
NOTES:
o Lowland tropics, temperaturas greater than 2>.5 C.
o o Mid highlands 18 e ta 23.5 C.
Eigh highlands 13 Oc ta 18 oc.
Cold or Paramo less than 13 Oc ~ REJEGTED
1. 23,5 oc. This has long be en che declared temperatura cutoff in the
classification of the pasturas programo lt effectively divides the
Llanos at Carímagua from the Cerrados at CPAC. GIAT Palmira is marginal
in this, with a mean tamp. of 23.4 oC. Above this temperatura in certain
moist regions beans can exhibit a completely different regime of disease
and pest attack.
9
2. 18 oC. This 15 just ahove the temperature of Popayan. Cassava and
Beans exhibít an environment genotype lnteraction at about this point.
3. 13 oC. This is the temperature 1imit fer cassava as calculated by
J.Cock and ourselves. At about this temperature a majar change occurs in
the bean varieties grown in the Andes. This 15 not far from the
temperature of Pasto.
Class 4. This class ls unsuitable fer all CIA! commodities apart from
very few high altitude beans.
3. Soil Acidity
Although the Pastures Program 15 aiming at producing varieties that
wi11 talerate soíl pH lover than the 1imit we propase, ve think lt ls
val id and conservative to set lt to pH 5.5.
l. Acid SaiIs. pH 1ess than 5.5.
2. Less acid and neutral 5011s pH ahove 5.5.
10
NOTE:
l. Many of che soils marked in chis study as having pH higher than 5.5
are very poorly drained. This 1s consequence of having Ca use che FAO
database as a first approximation.
4. Diurnal Temperature Range
Many people we have spoken to during chis analysis have been
surprised at the inclusion of this variable. Many fungal diseases are
highly sensitive to dew. J. Lenne and C. Lozano have both solicited
studies by AEU on chis topie and Dr. Lenné was convinced that this might
have been a contributory factor to the lack of adaptation oí the CIAT
legumes to CPAC, whereas they did well in che forest regions.
In Qur classification we have designated these Maritime . less than
10 Oc diurnal difference, and Continental far those areas with a diurnal
difference greater than 10 oC. The terms Maritime and Continental occur
11
frequently in climatologieal discourse. Ihey have been measured in many
different ways, We are proposing ta use che terms in a way ta cIarify a
recognized plant pathologieal concept and no't ta redefine the tenas
climatologicaly. Ye havo te have simple nam~~ ~_~ vur classes.
Classes;
L Maritime Less than 10 Oc mean diurnal ~emperature ranga
2, Continental o Greater than 10 e mean diu~al temperatura
range
5. Annual Temperature &ange~
o . íJe set the annual temperatura ranga at: 10 e, Previously the AEU
o had used 5 e as the range for cassava, Ibe largar annual range allowed
us to immediately e11minate 12 possihle climate classes as having
winters too cold for the majority of the crops ve would be considering.
Classes:
l. Tropical
2. Subtropical
Less than lOoe annual temp. ranga
More than lOoe annual temp. range
12
RESllLTS
In de.te.rmining criteria for selectiQn of activities in NR.11 che
ecónomist group has produced a list in three categories, Economic
Impaet, Equity and Environmental Impact. "!'he data were analysed using
the IDRISI image processing package to extract data from che enviro~~ent
class images in conjunction witb the demographic and income daca to
allow indicas te be construeted as measures under these categoríes.
Economic Impact
Areas of legally protected areas were masked out frarn the
environmen~al classes and valuas for the area of each class were
extractad. Areas with poor a.ccess were then masked out and the resulta~t
areas were extracted. A subjective product:ivity index was const.ructed
for :::he environment classes. This took values fraro 1 te 7 and "'as
contructed as follews:
Temperat:ure
Lowland
Med
HighIand
DRY SEASON
LT2 3 - 6
3
4
4
4
4
3
7 - 9
2
2
1
13
2 points were added for non·acid s011s and 1 peine for subtropical
areas, ro fO:(Ilt en index of potencial economic impact chis index was
multiplied by the accessible area of each class. Ta.ble 1 sho\¡,t$ the 47
classes ordered b;~ th:s i~ldex.
Equity
To achieve a crude asse$$mént: of an equity index ehe mean rural
income vas extractad for each elass. Ya wished ta rank this taking inta
account the rural populations of the clasees. !he importance for the
equity Lesue increases with number of people but it decreases as rural
income risas. Ye therefore divided total population by rural income to
obcain an inrlex increasing wieh importance for equity. Table 2 show$ Che
classas ordered by this indexo
Environmental Impact
Problems of environmental impact are not easy te estimate directly
from these data without further detailed knowledge of the regian, rhis
will be done in more detail on selecced regions in Phase 11.
Areas of high risk to problems of an abusive nature such as exeess
pesticide use will be in the aré" with acceSs to markets and hence
inputs, They will be the higher population areas within eaeh class.
tabIe 3.1 shows the area in each clan with rural population greater
tluin 20 per k:m2.
14
Nevertheless sorne attempt can be made. Araaa with relatively
untouched nativa vegetation. be it forest:, savanna or ochar type are
likely to be those with low rural populations. Tabla 3.2 sho\o's che cop
ten classes ordered by ehe areas of each clas!: ::-:: ..... population less tha-:-.
2 per km2. this can be read as either che afeas available for expansion
of agricultura, or as nativa vegetation fer protection.
Problems of depletion and eresien through insufficient inputs are
lesa easy ta estímates. \Je have mada ao approximation that they wil1
occur more frequently in settled areas. away from markets with less
incentive tú use inputs, An índex of the atea of each class witb
populations from 2 to 20 people per km2 divided by rural incorne. Table
3.3 shows the classes ordered by this index,
A furt.he.r consideration is our probability of success. 'rable 4
shows the are as by class under three of the CIA'r crops, unfor~unately we
do not have a complete or recent distribution of pastures or cattle,
Also sho",'n are the areas in square kilometers of each class with a
climate similarit:y index less t:han ,3 when compared to the major CIAr
stations.
Table 5 lists all of the classes that have appeared in the top 5 of
any of the ordered cables.
lABlE ,. Envil"Ql"l1lmt classes Qr</ared by proó.lctfoo j:X'!«!ntial irx!ex.
Class ..
2 TlSMA
5 TlSCA
17 1 M $; C A
8 TLSMW
12 TLDCW
9
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" l8 24
"
T lO M ~
T L $ e W
T L D C •
T L H M A
T L o M A
THOCA
'fIilSMA
T H ti e A
T M D e w T M O M W
59 SMSCW
16 TMHCA
23 ":'MSCw
20 TMSM\.'
60 SMOCW
13 THHMA
7 TLHMW
52 $HIiHA
"8 SLOC\.'
1> TMOMA
5l SHSIoIA
25 TIIKMA
54 SMO)CA
" TlHCA 19 TIoIIlJiIIW
29 T~SCA
36 TIiOC,""
lO ¡HOCA
44 SlSMW
35 THSCW"
26 T liS"A
22 rMHf:w 10 TlHC\.'
32 T HSMW
47 S l S C \.1
.42 SlOCA.
58 $MHCU
3l T IiDMW
27 TMDMA
4
4 , • 4 , • , , , 2 , 4
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56 SMSHW 6
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J4 Tlltltw .. T *' Tropical,
SU1I. Iturat Urben ..... , "", ... Rural Nl..II'Í>ef"" ÁCcessibL Act. are >eN
No' J>rQter«t
Prtld. Popo Pq>. PC! 0# area C')Jtsicte
'''''', mean ei:U'!tries Bra2i l ",2 ""
3242757 14623&4 12830741 1936433 4496741 8Ol7021 1841765 7133111, 23632159 18191)42 5860458 899556S
1503994 .4704a45 t072!149
3 3 8
12 T ,. 1364902 ~SSO
10851as 4577921 1061534 3471035
97f1J2$ 2234896 853181 4122772
ns071 3379676 590522 4810238 513443 21,32653 S49:¿ZO 203ó116
521742 254406l
462029 447963 45?0á7 1149785
453819 2335137 437612 2747(:.1.0
43131.2 498t.2
349613 2391089 za7íl61 1118344
'95558 21ml 1951.72 1á366S 191606 2053693
150799 396976
'45t49 681450 143158 34425
14133a 272610 l36304 634496
130279 1391017 66$12 674154 65748 22310SS
54394 257437
51424 388&00 47822 115139 40546 18239<1
3V861 312785 290'3 425916 25941 73926
24703 44847
20811 55395 16947 194684
10877 552127
11475161
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T l S le A 746Z3S4 T L D lo! W 6264550 T l '$ M W 586tv.58 T l. () "'1 A 412.2m T lo! S e A 7133114
i H o M W 2544063
T l e e 4 4496141 T M S M A 4810238 ; l H ". A 2234896
7 L S e ~ 4577921 r ~ o e A 2231058 , M S M 101 2747640 .... o C \J 4704845 T M D M A 2053693
T M DCA 337'9676
T :. f} e A 3471035 T M (l e Ol 206116
T lo! H lo! A 2391009
1 L K '" ~ 1378344 T lo! S e w 2335137 r H s C A i'397t:ll1
T k 11 e A 2432653 t H ti e J
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T M If e W
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552127 ,...,. 715139 681450 425976
3lms amiO , ...... 257437 '396976
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31 T 11 )1 i' W SOOO7
47 S l S e \J 73926 34 fllIlC\I al597
48 SlOCW 103665
42 SLOCÁ 44847 58 SMKCW 5539S
56 SM$MW 50802
60 SMf}C\J 49842
54 SMD~A 34425
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6912 .,,74 6663 6553
5677 ,,.. ''''' 4998
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100 70164 79 14W9 63 16768
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t!12S6 b2645SO 11415161
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lZ 14
13 ,. )
•
Rl,¡r.l 1hKIIl PCI pe!
.en stt:!.
1m m 453 954 &30
734 ... 381 .1> 541
547
492
:m 7., 487
438
"'" 1ro
"'" ...
._, " ,. U 24 13 23 21 17 ,. ,. "
Access· ¡bIt!
615922 341225 410689 m ... 303174 ,-, , ..... '30436 <84'08 426590
Acc. are Ares Total area Out$ide Not
Sra%. ¡ L Protected
1081~
1966HI
29'I3ll3 n1921 244770
84:198
'20358 Z6846
131740
'954211
846215 912817
391260 398355
2'31409 2800366 108m e30303 493803 54CJ4M
338878 4139«-
344035 390481 137627 117?6l
1433711J 1576MO
514077 557513
lAStE 3.2. Areas in each dass that ere not teptly protectect M hava hbd relatively lit!:le disturbance
Ctas!! ,o. Olsturban arel "Km2
Rural
!'<p.
Urben
1'Qp.
2 r L S M A 2tl2i,SlS 74ó23&. 1283{)141
5 TLOtA 1110909 4496741 &:137021
T l ¡¡ M A 1052434 2234a94 V'9a926 6 T l ti e A 431.984 1471035 8324097
1Z 17
• 4
TI.DCli
T M S e A
1 l 5 ¡.¡ W
Tl¡,CA
TMOCA
415629
382568 }O4150
';C8!J5
Z!52S5
4704845 10128149
7;33114 l3632759 5a60458 8995565 Z7l/.;10 :wzaa6
3379676 8204852
~ 1 T l S C IJ Z25091 4577921 azm79
3 3 2
4 7
• " 1
1 1l
Rvr.L PCI
29l! SSIl 111 651 161 541 487
l'J7 .., "'"
24 ,. 18 lZ 1l ,. 23
" 12 17
Aecess f· Acé. ere ble Mside
Total
arl,l4
erea Brazil PrQtecred
810689 299383
464108 131740
325642 14Z930
530767 73349
375999
61"5922 303174
47113 36>535
171921
108109 Z44770 2_ 85m
2431409 <1'800366
1433703 1576880 115760, 16Z4899 784066 879678 mm 846215
4_' "",na
483141
""")3 912817 ,,_ 3M"" 4_e
lABLE 3.3. Area by class witn lH::eLy degradatton by rutdent depl«ttcr¡ (er051on or nutrient 1eachins. wrud infestatim,
etc)
Class Nutrient Rural Oeptetion Popo
Oegradation
Urben
pO!'.
2: TLSHA
3 TtDMA
9 Tt(¡MIJ
5 TlDCA.
17 T M S C A
6 T lOCA
21 TMI)MIJ
15 TI1t1CA 12 TLDCIJ
1 fl HMA
792 7462384 12836741
517 4122172 7077859 473 6264551l 11475161
449 4496741 8031021 427 11n114 &32.759 386 3471C!l5 8324097
306 254400 4134194
m 3319ó16 82_2 ID 4704845 10728149 :!35 2234896 27l>89Z6
3
• 16 3
• 4 ,. 7 7 2
"".1 PeI
..... " of
IheM std, cOlIltries
45l
54' 523 675
1032 ... 381
826 954 194
298 460
492 ,.. 541 651 170 .. 5 761
'"
24 13
" " ,. 'Z ,. 12 13 ,.
Aecessibl ,,~. are
area Outsidct ..... .. ,
8ral j l Protecte<.l
810689 426590
341225 484108
615922 5307067 130436 362S3S 375999 32S64Z
29'I3ll3 195420
1%610 131740
108109
7334. Z6846
8Sm 111921 142931)
2431409
51'077 391260
14337'03 846215
784066 137627 '83141 108m
1157602
Total
""
2IlOO366 5$7513 396355
15768BO 912817 8?'9678 T37Vó3
499928 830303
1624899
rABiE 4. Envi ronuent CllIsus ardered by present relevance ta CIAT crop$.
Class
17 THSCA
6 TLOCA
2: TLSMA
5 TLOCA
18 TMDCA
12 TlDCIiI
3 T L tl 1( A
9 r LDMW
8 TLSMW
" TMSMA 16 TMtlCA
28 THHCA
21 T M D M W
11 TlSCW
23 T M S C W 24 ~M!lCIoi
20 THSM ....
15 T M tl M A
13 T H H H A
'; T l H M A 29 r Ii S e A
52 SMHMA
53 SKSMA
59 SMSCIJ
7 T l ti M W 25 rliltMA
60 SMOCW
lO r H D e A 19 TMliMIoi
36 THOCIoi
26 THSHA
32 THSJilW
4 TlHCA
22 TMHCIoI
42 SlOCA
35 lHSCW
56 S MSMW
48 S l G e W 27 THGMA
56 SMHC ....
1.4 SlSMW
54 S M tl M A 10 T l ti C W
33 THOMW
47 S L S C 101
31 1 11 H'" W 34 TtlKeU
57 SMOMW
ft 1 ce 8eans Yuca SU:Imed .1000t1a .1GOOha J(lOOOha ct"Op
arft CAdaqus Palmi ra Qui 1 i chao PopA""n la Libertad
9'" Sl' 64. 844 390
m 3l!2 274 383 ,74 8l 90 2.
225 93 34 38
" '" 83
20 13
" 51
60
:i2 33 ,
5
e 5 1
9
13
2 o
'4 , o
" • 6 3
• 1
• • •
.,6 87 ,.. 34
74 302
.. 63 "6 38 30' 46 79 113 ,,. .. 5' 138
149 107
246 " 248 31 191 107
4. " 121 19 175 ZO 73 60
105 48
21 71
4 " 67 2:1 49 37
7 " 1 23 , ,
16 20 11 10
" 3 6 25
" , 17 1 16 5 4 6
5 3 16 ,
" , • 2 14 ,
14 , · , 2 • , . 2 , 4 , , 1 , , , , · ,
1810 o 1063 33é 1025 84S183 995 111508 876 o m 1341 574 o '06 o 492 "3871
"'" o '06 • ,.., o 324 , 292 26665 2J3 ,
2J2 • 171 o 165 o 150 o 14\ 82397
'06 o 99 •
77 •
" , 70 , 68 ,
'4 , 47 ,
'" , " , 23 o 22 • 2' 341 21 , la ,
17 • ,. , 15 ,
" , 12 o 11 o 6 ,
5 o 4 o < , . , • o , .
=9 31162 7096 1000 3347 12567 7127 -16582
34' o 4058 1693 5735 o 6410 337 ,... m.
o 2040 o 681
• • lOS\ 341 ?ro7 5362 340 340 681 1008
a 1360
", . o • a 8117
• • o • o • o •
• 324 · , · , • • • 341 • • • o o O o 6138
• ID o • o • , , O , , , O ,
• • o •
• 323 o • • • , . · , , .
342 •
• o • 32546 · "" , , , , , , · , o 6302 · , · , o , , , o '''' , .
341 , , , o , o o o 2377
2Ja5 o , o , o · , · , o o , O
2JU ,
• O 342 o ,,., o · ,
• 34' , , • o. , , , o , O
682 , , . , o
• o • o O O o O o • , O , .
TABLE 5
Class
1
2
3
5
6
8
9
12
17
18
Occurrences of classes in the first rows of the ordered
tables,
1 2 3.1 3.2 3.3 4
.. .. .. .. * .. *
.. .. .. .. .. ..
.. .. .. * ..
.. .. .. .. .. .. .. .. .. .. ..
..
o 0 .. 2 •
o Cl_t •
¡
o ..... .
o •
o •
• :-.. .
CJ _.. .
Drs. Luis Sanint. W. Janssen. Nay 15. 1990.
Methodology for ranking LAC environmental classes.
From the various categories identified by P. Jones and D. Robinson (J&R) to rank environmental classes, a single ranking index was developed. The three basic criteria (growth, equity, sustainability) haYa been broken into the fol1owing categories:
A. Growth category. It has two components: (i) the production potential component, as def1ned by J&R (accessib1e area times a subjective productivity index) and (1i) the growth potential index, whieh expands the former concept to account for population density, i.e., the more densily populated a class is, the higher the mUltiplier effects of infrastructure, labor, resource availability, etc. The idea i5 that currently populated areas have more growth potential than those in the outside frontiers.
8. Rural Poverty Cateqory. Table 2 in J&R divides rural population by the square of the rural Per Cap ita Incomé. Here J it was redefined to exclude the rural population siza in each class and , in turn, include the density of population divide by pe!. It is argued that area size was already sUfficiently ineorporated in the growth potential category and total population is highly correlated with area size.
c. Environmental Category. Tables 3.1 1 3.2 and 3.3 in J&R were included but the areas in 3.1 and 3.3 were multiplied by the subjective productívity indexo This gives more value te more productive hectares at rísk, relative to the less productive anes.
In addition to those three criteria, the list was extended to ponderate factors like ei) number of countries in each agreecological class, (ii) percentage nf the area in that class currently occupied by the three CIAT crops (beans, cassava and rice) and elil) the accessible area in each class outside Brazil.
The single ranking index has two basie charaeteristics:
1.- All the scores in the various categorías were standardized (Substracted from the category mean and divided by the standard deviation). This yields a unitless index that allows intercategory comparisons.
2.- Subjective weights were applied to those standardized indexes, maintaining a balance among the majar criteria already identified by Jones and Robison: growth, equity and sustainability. Each group reeeived weights amounting to 10 points. A sensitivity analysis of those weights reveals that the optimal set is quite stable to changes in the various weights.
Environment Classes ordered by weighted coefficients weighted Scoring
Class Coefficient Hierarchy Scenario 1
S T L S I!W 67.77 1 Weights 2 TLSI!A 65.86 J 4 Prado Potential 9 TLDMW 57.54 3 6 Growth potent.ia
17 T M S C A 39.25 4 20 T M S M W 31.41 5 10 Rural Equity 11 T L S C W 31.07 6 12 T L D C W 27.92 7 Environment 2l TMDMW 24.94 8 5 3.1 ;; T L D e A 23.S1 9 1 3.2
14 TMSMA 15.62 10 4 3.3 23 T M S e w 14.78 11 32 T H S M W 10.04 12 3 Number Countr. 13 TMHIIA 8.49 13
3 T L 1) M A 7.04 14 5 % CIAT com:nodi'i 24 T M D C W 3.01 15 19 T 11 H M W 2.30 16 5 Area out BraziJ 28 T H H C A 1. 69 17 15 TIIDMA -0.6<1 la 56 s M S M W -0.72 19
7 TLHMW -1.00 20 1 TLHMA -1.29 21
27 T H 1) M A -1.45 <12 34 T H H C W -2.03 23
6 T L o e A -2.44 24 30 T H 1) C A -2.44 25 lB T M D e A -2.70 26 16 T M H e A -5.61 27 36 T H 1) e W -6.84 28 33 T H 1) 11 W -7.41 29 35 T H S e W -7.95 30 31 T H H M W -8.95 31 29 T H S e A -11. 25 32 22 T M H e W -12.23 33 44 S L S M W -15.34 34 10 T L He w -15.92 35 25 T H H M A -17 .16 36 59 S M S e W -18.111 37 26 T H S M A -20.29 38 53 SMSMA -23.37 39 52 S M H M A -25.25 40 60 S M 1) e W -26.70 41
4 T L H e A -29.02 42 47 S L S e W -29.37 43 42 S L 1) e A -29.38 44 48 S L 1) e w -31.82 45 54 SMI)MA -35.$7 46 57 S M o M W -39.$0 47
nvironment classes ordered by weighted coefficients
lass Weighted scoring
Hierarchy Scenario 2 coefficient
9 T L D M W 47.99 1 Weights 2 T LSJoIA 44.48 2 4 Prod. Potential 8 TLSMW 41.16 3 6 Growth Potential
n Tl!SCA 28.71 4 20 TMSMW 26.54 5 10 Rural Eguity 21 TMDJoIW 23.89 6 11 T L S C W 19.66 7 Environment 12 TLDCW 17.37 8 5 3.1
5 T L DCA 13 .50 9 1 3.2 34 THHCW 11.56 10 4 3.3 32 T H S M W 9.33 11 23 TMSCI'I 9.29 12 O Number countr~ 14 TMSJoIA 7.84 13 19 THHl!W 5.57 14 O % CIAT Comrnoditie 13 Tl!HMA 5.45 15 27 T H D M A 5.38 16 O Area Out Brazíl 30 T H DCA 4.56 17 31 THHMW 4.09 18
3 T L D M A 3.98 19 15 T M D l! A 2.08 20 24 T M D C 1'1 1.91 21 28 T H H C A 0.94 22 33 T H D M 1'1 0.90 23 36 T H D e 1'1 -0.35 24 35 T H S e w -1.85 25
7 T L H H W -2.62 26 6 T L DCA -3. J8 27 1 T L H M A -4.14 28
18 T M DCA -5.54 29 10 TLHCW -7.68 30 44 S L S M 1'1 -7.72 31 29 T H S C A -8.70 32 25 T H H M A -U.65 33 22 Tl!HCW -12.84 34 16 Tl!HCA -13.22 35 26 THSMA -13.65 36 59 s M S C W -16.93 37 47 SLSCI'I -18.11 38 53 S M S JoI A -19.18 39 56 SMSMW -19.47 40 52 SMHMA -22.16 41
4 TLHCA -23.25 42 60 SMDCW -23.37 43 48 S L D e W -23.77 44 42 S L D e A -24.55 45 54 S M D M A -25.24 46 57 S l! D M W -25.93 47
Environment Classes ordered by weighted coeffic1ents Weighted Scoring
Class Coefficient Hierarchy Scenario '3
S TLSMW 91.59 1 Weights 2 TLSMA 85.12 2 8 Prod. Potentia 9 T L O M W 83.04 3 12 Growth Potenti
17 T M S e A 59.01 4 II T L S e W 43.17 5 10 Rural Equity 20 TMSMW 42.31 6 12 TLOCW 39.01 7 Environment 21 TMOMW 31.80 8 5 3.1
5 T L O C A 31.29 9 1 3.2 14 T M S M A 20.84 10 4 3.3 23 T M S C W 20.71 11 13 TJI!HMA 12.54 12 3 NUlllber Countr.
3 TLOMA 12.21 13 2S T H H C A 9.41 14 5 % CIAT Commodi 24 T M O C W 5.72 15 32 T H S l! W 4.24 16 5 Area out Brazi
6 T L O CA 0.84 17 1 TLHl!A -0.77 lB
19 T JI! H JI! W -1.34 19 18 T l! O C A -1.36 20 15 T M D M A -3.24 21
7 TLHMW -3.60 22 16 T M H e A -7.03 23 30 T H D e A -8.23 24 56 S M S M W -8.57 25 27 T H D JI! A -9.18 26 34 T H H C W -10.29 27 36 T H D e W -13.05 28 35 T H S e W -14.17 29 33 THOMW -15.06 30 29 T H S e A -15.23 31 31 T H H M W -16.81 32 22 TMHCW -19.46 33 25 THHMA -20.75 34 59 SMSCW -21.12 35 44 SLSMW -21.57 36 10 T L H C W -23.24 37 26 THSMA -26.72 38 53 S M S M A -28.91 39 52 Sl!HMA -31.32 40 60 S M O e W -32 .10 41
4 TLHCA -36.26 42 47 S L S e W -37.02 43 42 S L o C A -37.46 44 48 S LO C W -38.42 45 54 S M D M A -42.90 46 57 S M O M W -47.79 47
;ironment Classes ordered by weighted coefficients Weiqhted scoring
Hierarchy Scenario 4 .ss Coefficient
2 T L S M A 50.02 1 Weights 9 T L D M W 48.42 2 4 Prod. potential 8 T L S M W 47.50 3 6 Growth potential
L7 T M S e A 37 .69 4 ¡o T M S M W 31.ll 5 10 Rural Equi ty 11 TMDMW 26.93 6 L1 T L S C W 23.01 7 Environment l2 T L D e li 20.42 8 5 3.1 5 T L D e A 18.93 9 1 3.2
23 T M S C W 15.58 10 4 3.3 l4 T M S M A 15.22 11 32 T H S JI W 13.36 12 3 Number Countr. l3 T M H M A 9.65 13 19 T M H M W 5.17 14 5 % CIAT Contmoditie
3 TLDMA 4.38 15 28 THHCA, 4.30 16 o Area out Brazil ;6 s M S M W 2.99 17 l5 T M D M A 2.36 18 27 T H D M A 2.11 H 34 T l! Il C W 1.68 20 24 T M D C W 1.58 21 30 T Il DCA 0.22 22
6 T L D e A -1.10 23 7 TLIlJlW -1.20 24
l8 T M D e A -1. 77 25 13 T Il D M W -3.96 26 36 T Il D C li -4.19 n 1 T L Il M A -4.57 28
l6 T M H e A -4.75 29 35 T Il S C W -4.99 30 II TIlHMW -5.31 31 22 T M H C W -9.03 n 29 T H S C A -9.15 33 14 S L S M W -12.49 34 la TLHCli -12.83 35 25 THHJo!A -14.29 36 26 THSJlA -17.10 37 ;J S M S Jo! A -21.19 38 39 S Jo! S C W -22.31 39 32 S Jo! Il Jo! A -22.41 40 12 S L 1) e A -26.05 41 !7 S L S e W -26.05 42 4 TLHCA -26.59 43
la s Jo! o e w -30.01 44 18 S L o e W -31.28 45 ;4 s M D M A -34. :lB 46 ,7 S M D M W -35.81 47
Environment Classes ordered by weighted coefficiants Weigbted Sooring
Class Coefficient Hierarchy Scenario 5
8 T L S M W 88.04 ~ Weights 2 T L S M A Bl. 70 2 4 Prod. Potential 9 TLDMW 66.66 3 6 Growth Potential
n T M S e A 40.S1 4 II T L S C W 39.14 5 10 Rural Eguity 12 T L D C W 35.43 6 20 T M S M W 31.72 7 Environment
5 TLDCA 28.68 8 5 3.1 21 TMDMIV 22.96 9 1 3.2 14 T M S M A 16.01 10 4 3.3 23 T M S e W 13.97 11
3 T L D M A 9.69 ~2 3 Number Countr. 13 T M H M A 7.33 D 32 T H S M IV 6.72 14 5 % CIAT Cornmodicie 24 T M D C W 4.45 15
1 T L H M A 1.98 ~6 10 Area Out Brazil 19 T M H M W -0.5B ~7
7 TLHMW -0.80 lB 28 T H H C A -0.92 19 15 T M D M A -3.59 20 la T M DCA -3.64 21
6 T L DCA -3.78 22 56 S M S M W -4.43 23 27 THDMA -5.01 24 30 T H DCA -5.10 25 34 THHCW -5.74 26 16 TMHCA -6.48 27 36 T H D e W -9.49 28 33 THDMW -10.B6 29 35 T H S C W -10.91 30 3l THHMW -12.59 31 29 T H S e A -13.36 32 22 T M H C W -15.42 33 59 S M S e IV -15.51 34 44 S L S M IV -18.19 35 10 T L H C W -19.01 36 25 THHMA -20.03 37 60 S M D C W -23.38 38 26 T H S M A -23.47 39 53 SMSMA -25.55 40 52 SMHMA -28.09 4l
4 T L H e A -31.45 42 48 s L D C W -32.37 43 47 S L S C W -32.6B 44 42 S L D e A -32.72 45 54 S M D M A -36.97 46 57 S M D M W -43.19 47
.
sQlvte numbers for eaeh ~.tegory~ by ~t.$s.
0$'
1 lLMHÁ Z TlSMA 3 TtIH,. '" . T l M e A 5 1 l ¡) C A 6 TLDCA 7 T l 11 H lo!
a TLSMW () TLtllll10l
10 TLI!CW
" TlSCIo! 121ltlCW 13 TM'I"A 14 TMSHA 15 T M o M Á
16 T M H C A 17 T" S C A 18 T M o C A
19 T M M " ti ~C tMSMW !1 rMOMW :2 TMMCIoi
~ fMSCW ~4 fMOCIol !S fI!HM:* !6 fH'SKA !7 THOMA ~8 TltlfeA !9 TI!SCA ;0 TIlOCA ;1 TIIHMW :, fllSMW
:J feOM'" :4 fHHC'" oS THSCW ó TIiDCW 2" SLOCA 4 SlSMIoi
7 StSC'"
a SLDCW 2. SHII'MA 1 SHSMA lo seOMA 6 SMSMW
7 SMOMW
9 SMSCV o SIIDCW
ProclJctian Growth Eqvity Enviromental Tabte$ wLtllber XClA.i Prod.Pot. f>ot-e!'ltial PotlltAti.t Indo,ou: 3.1 3.2 3.3 COW\tr. COImIod. OUt Irazi
976925 3242757 SS3l81 1413:38
1936433 10615310-287061
1819042 1364902
39867 1085185 1503994
310-9613 590522 191606 457O.!1.7
1847765 725071 136394 437612 521742 ,"0546
453819
5492'" 145149 47822 1!lSn
513443 130279 65748 B06ó
29013 16947
'981 51424 66512 2471,}3 54394 Z5941
195472 1"95:558 150799 1431SS
"" .. 3'04
462029 431312
U411¿o 6100548 6355947
168410 3130616 3949002 3036W
16126036 19506121
573597 , . ......,. 1'915689 781 .... 7605132 3456101 3154257
lZ905429 4026611 2937470
12638770 916S456 640699
aTl'58S3 sam:sl 29.3024; 12"16193 3938\6
96327tl,} 2709303 1617955 305:322
1780256 429205 :14m
'36m1 1300012
104S5 t:538184 :'580640 412684 807017
1421333 95518
30481:2 2452
2524412 2321)47
4.9 ... 14.8 1.1 4.6
5.' 29.4 'S.8-
'M 40.' 15.7 1 .•
29.' 19.3 4Z.9 6.7 8.2 8.S
sa.5 53.2 48.S 29.7 27.5 ,(J.5
16.6 24.5 76.6 12:.6 26.S 65.9 74.3 80.0 65.3 94.2 52.0 55.0 3.'
,8.8 18..2 1.4 3.0 6.' 0.3
15.1 •• 6 2.' ..,
844" JG4016
703S. 5019
159280
688'4 73255
376938. 325024 , .... 29nn ,..576 lOmo 179U4
.""" 47700
296361 71970 4311'SZ
118Z55 15_
S79. 148790 ""'16 35076 11344 7893
8D268 35932 29159 '008
21056 al(lO 1980
22192 25M
96<1 15155 6468
6'" 6025
26704 1920 .... 4545
39930 o
1052434 2024818 211118 25080S
11109Q9 434984
""'" 304150 ,,,.... 61>30
225091 41_ 31595
159827 14015
"620 3112S .. 225285
2992 ,-7838 266Z
16231 , .... 5161 9412 1651
260" 17917
26'07
• 1009 2594 341
1612 l!633 -310 1238 ,-
10715
"'S mJ
o o
484' 75'.
704 3'66 10"
85 1791 ro 404
133' , ... 5.
64" 1131 343
'86 lS2 '80
1281 583 267 ...
1230
•• w no '05 31 11
". 13'
•• 8
13 11
• 19
'00 11
" 11 13 85 66 2 ,
13 47 12
27 82186 ,S6Z71 444
,. 24 13 12 ,. 12 ,. 23 12 1
17 13 18 21 10 n 18 12
• '7 10
7 ,. • , 8
6 10
• • 3
• 7 2 6 6 3 2 2 4 3 3 3 , , 4 ,
10
0.04~ 428791 0.13% 1197533 O. 13% 390S40 0.04% ~ 0.2t% 526961) 0.20% 146698 (l.12% 2401lD (1.16% 1:468621 0.1$t. 7'86440 0.06% 39867 0.161 122148 (l.21X 687686 0.17% 157729 O.m 25289S 0.11X 46913 0.36% 175674 0.30% 324328 0.24% 171557 0.1n 52956 0.20'% 247240 0.2:5% 10718S 0.31X 33424 0.26% 179246 0.17X 316552 0.19% 53171) 0.10'%. 31925 O. \3% 10877 0.26X 69191 O.17X 99183 o.on: 66089 0.00% 6069 0.30% 25390 o .on: 17814 O.OOX 19B1 O.l~ 41636 iLnx 66512 o.~ 247U3 0.14% 54394 0.05% 25942: 0.04:1: 195470 o.zs::;; S51SO 0.2OX 95472 0.01% 143157 0.90% 1830 o.óO% 3104 ó.1~ 436909 0.06% 43131Z
(l.1 7X 228685
Standerdized $Corín; coeffictents ~trjx
taasa
1 TlHMA 2 TLSJIlA
3: TLnM" 4 TUtCA S TLnCA 6 Tt.DCA 7 TLH/IIW
8 1l.S"W 9 TlOIU'
11} TLI:IC\I 11 TLSCW 12 T l. j) C W
13 1M""A 14 TMSMA 151MDM;' 16 TMHCA
17 TMSCA 1fl TMOCA 191M H M W 20 T M S JC W 21 TIiIUMW 22 ¡"HCW 23 TMSCW 24 TMntw
25 T ti Ir " A 26 T H S M A 27 THOMA 28 THHCA 29 1HSCA 30 THDCA
31 T k H M W 32 TIIS"W 33 TIIO"W 34 TIIHCW lS THSCW
36 TIIDCW 42 S L D e A 44 51.$MW 47 S l. S C W 48 SLOCW 5'2 SMIiMÁ S3 iMSMA 54 S/IIO/llA 56 SM!iNW 57 SMOMW 59 SMSC\I 6IJ 5MbCW
Produetion Growth Equity EtwirOl'lllll'lteL Tables Cou'ltf. in Cl'u Outsidt Potftlti.l Potentiat Index 3.1 3.2 3.3 in eLallS COIM. 8ruH
0.12 4.14 0.53 ~0.$4
2.17 0.85 ~C.32
1." 1.31 ~0_69
0.80 1.52
-0.23 0.14
-0.46 ~0.06
2.04 0.34
-0.55 -C.09 0.03
-0.69 -1l.07 0.08
-0.53 -1l.68 -0.74 0.11
-0.56 -0.65 -0.14 -0.71 -0.13 -0.75 -tl.68 ~O.65
'0.72 -0.67 -0.71 '0.46 ~O.46
'-0.53 ~O.S4
-0.74 '0.75 -0.06 -0.10
-0.39 0.45 0.51 ~0.85
-0.20 -0.02: -0.22 2.64 1.M
-0.76 1.43 0.85 •• Ir! 0:/11
-0.13 -0,19 1.94 ....
-0.24 1.88 1.1'2
~o_ 74 1.03 0.40
-0.24 ~O.62
·{l.SO 1.aI
-0.29 -0.53 -0.82 -0.49 'D.79 -0.88 ·c.s9 ·O.6() ~0.81
-0.59 -0.80 -0.79 -0.71 ~~.57
·n." -0.82 '0.88 -0.33 -0.83
-0.89 -0.31 -0.~9
-1.02 ~0.90
·0.88 0.10
-0.33 0.15 0.56
-~.45
-0.31 0.11
-0.31 .... -0.81 -0.76 ·0~74
1.21 1.06 .... 1).11 0.02 ·~.26
-0.42 ·O.lD 2.00
-0.56 ~0.01
1.56 1.90 2.13 , .54
2.1. 1.01 1.13
~O.93
0.47 ·0.3S -1.03 -0.96 ~0.81
~1.01
-0.48 -1.06 ~0.97
·1.07'
o~oz
2.20 -0.04 -~.74
0.76 -0.13 -0.09 2.92 2.40
-0.62 2.1.3 1.84 •• 25 .... -O~14
-0.34 2.12.
-0.10 -0.39 .... o:"
-0.76 .... .. ,. ~0.47
-0.64 -0.74 ~O.02
-0.44 -0.52 -o. n -0.60 -0.13 -0.79 -0.S9 -0.56 -0.80 "0.66 -0.75 ·{l.15 ' •• 15 -{l.55 -0.19 -0.73 -0.71 -0.42 -{l.!l
2.4& 0.41 S.16 4.30 0.17 ~.91
0.26 -0.51 2.64 2. t4 0.71 0.52
·0.28 -0.06 0.41 1.41
-0.14 2.Z9 -0.41 -(1.6' 0.19 0.32 0.12 1.08
-0.34 -0.16 0,01 0.22
-0.39 '0.15 ·(),16 -0.42 0.63 1.32 0.19 Q.«;
-G.4Z -0.28 ·0.3'1 O.lB -0.41 1.24 '0.42 ·0.63 -(1.39 0.06 -0.32 G.44 -0.42 ~0.S4
-11'.41 -0.65 -0.43 -0.69 -0.36 -U.15 '0.38 -0.5<1 -í:t.36 -0.58 '0.43 -0.69 ~0.43 ~o,.6a
-0.42 -0.69 '0.43 -0.70 ~0_43 -o.sa '0.41 -0.S4 -0.42 -0.69 ·0.43 -0.62 -0.43 ~O.68
'0.40 ·0.68 -0.40 -0.51 ~0.42 '0.60 -0.42 -0.70 -0.43 -Ó.1'O ~0.41 -0.68 -0.42' ~0_63
-0.41 ·0.68
1.37 2.35 () .SS O.M 1.37 •. M , .114 2.19 •. M
-0.44 1.20 O.SS 1.37 1.86 0.05 e.s5 1.37 •• 38
-o. ti 1.20 •• 05
-0.44 1.114
-0.11 -o.n ~O.za
-0,61 •• 05
-0.11 -0.28 -1.1(1 '0.28 -0.44 '1.26 ·0.61 -0.61 -1. 10 -1.26 -1.26 -0.93 -1.10 -1.10 -1. 10 -1.26 -'.26 -0.93 -0.93
~0.91
-0.31 -0.25 -0.90 0.27 0.21
-0.34 -0.05 «0.14 -0.71 -O.OS •• 28 O.OZ 0.36 •• 02 1.35 0.97 0.53
-0.01 0.19 0.54 1." •• 64 0.00 0,.13
-0.52 -0.29 0.64
.-1).02: -0.70 -1.22 •• 91
~í:t.71
-1.22: '0.26 '0.40 0.36
-0..20 -0.33 ~0.94
0.61 0.26
-1.13 5.25
-1.22 ~0.S2
~0.77
0.65 3.11 0.53
'0.49 •• 9<1 ~O.27
0.04 4.05 1.82
-0.61 1.61 1.50
-0.23 0,08
MO.59 '0.17
() .31 -0.19 -0.57 .... -0.40 -0.64 -0.16 •• 29
-0.57 -0,64 -0.71 '0.52 ·Q,4j!
-0.53 -0.73 -0.66 -0.69--0.74 ~tl. 59
·0.53 -(1.67 -0.57 -0.66 -0.11 -0.51 -0.44 ·0.21'1 -0.74 -0.74 .... ....
hted StMdardhed Soof"'1nv ~ffi(;ients "'atrix
ective Waight • • 10 5 1 , 3 5
(Seenario 1)
• Prodl.Jction Growth Et".IIty Envíf"'OI'1l'I$I'\tat Tablas N".t,,, %elAT Msidc TOTAl.
Potentill pot$l1tial ,- 3.1 3.2 3.3 counr. e ..... Bruil 'COR' r 1. M " A 2." -2.36 -a.as O. '1 2." ,..4 4.10 -4.S3 3.27 ·1.29
T 1. S M A 16.56 2.711 ·S.13 10.98 S.16 17.21 7." -1.53 15.$4 65." T Lf)MA 2.14 3.'" ·4.90 -0.19 0.17 3.73 1." '1.24 2.65 7.04
T Lile A -a.16 -5.08 -lD.18 -3.82 O.,. '2.28 1.14 '4.49 -2.43 -29.02
T L ti e A .... -'.20 '3.99 3.81 2.64 8.55 4.10 1.33 4." 23.81
l' L o e A 3.40 -0.12 -8.84 -0.66 c.n 2." 1_14 1.14 -1.34 -2.44
TLIIMil ~1.28 -1.32 0.96 -0.44 ·0.2a ~O.26 3.12 -1.69 0.20 -LOO
T l. S N W 7.'" 1S.8S ·3.24 14.S8 0.41 5.63 6.51 -0.24 20.27 67.11
T L o M W '.23 20.28 1.46 12.02 -0.14 9.14 1.14 -0.72: 9.12 57.S4
T L H e v ~2.77 -4.5$ 5.59 '3.08 ,0.41 -2.46 -1.32 ·'.al -3_09 -15.92
TI.Se ... 3." 8.55 ~4.55 10.64 tl.19 1.29 3.61 -0.27 e.07 31.07
T l D e w •• 07 5.08 -8.06 9.22 o.n 4.34 1.64 1.42 7.SO 27.92'
1 M H M A ~0.90 4." ,. l' 1.27 -0.34 ~0.64 4.10 0.10 -l.16 8.49
T M S'" A O.SS 4.61 -3.08 .... 0.01 .... 5.58 1.19 0.40 15.62
1 M o M A ·1.86 -0.77 6.39 ~O. 71 ~0.39 -OT5S 0.16 0.12 -V17 -0.62
1MHeA '0.25 -1,'6 -8.15 ·t.71 -0.18 -1.67 \.64 6.74 -0,.87 ~5.61
T M S C A 8.14- 11.62 • 7.57 10.60 0.63 5.29 4.10 4.a7 1.56 39.25
TMnCA .. 36 -0.02 -7.45 -0.51 0.19 O ... 1.14 '.63 -0.93 -2.70
1MKM\I ·2.19 ·1.45 12.68 -1.93 -0.42 -1.12 -'0.34 -0.06 ·2.B7 2.30
1 M S JiI W -0.31 11.27 1GS5 4.75 -ú.39 o.n 3.61 .... 0.30, 31.41
T M D N W a-. l' '.n 8.64 3.83 ·0.41 4.'" a. '6 .... ~t.96 24.94
T M 11 e \1 '2.77 '4.46 1.10 -3.18 -0.42 -2.50 -1.32: 5.13 -3.19 -t2.23
1 M $ C W -0.27 6.21 0.2<l 3.30 -1').39 0.24 ' 3.12 3.18 -0.81 14.18
TMilCW 0.30 2.41 -2.61 '.39 '(U2 1.74 -0.34 0.D1 l." 3.01
1MlfMA -2.14 .1.46- -4.16 -2.33 ,0.42 -2.15 -2.31 0.67 '2.87 -17.16
1 H S K A '2.72: -3.71 -0.99 -3.21 -0.41 -2.61 -0.83 '2.62 '3.18 -2U.29
T " ti '" A '2.95 -4.18 19.95 ·3.6& ·!U3 -2.74 -, .82 .\ .45 -3:56 ·1.45
T I! !I e A 0.45 7.n -5.1'9 -0.09 ·0.36 -0.60 G.16 3.20 -2.61 t.69
T I! S e A -2.23 -1. 75 -0.07 '2.29 -0,38 -1.99 -0.34 ~0.t1 -2.11 -n.2$: T H ti e A -2.61 -3_18 15.65 -2.62 -0.36- -2.30 ·0.83 -3.52 -2.66 -2.44
T ti IH!IoI -2.96 -4.90 19.01 '3.87 '0.43 '2.76 -3.30 -6. '0 -):.64 -8.95
1 H S M \o' '2.84 ~2.97 21.32 ·3.G2 '0.43 -2.73 ~0.83 4." -3.32 10.04
r H o Iil 'W ·2.91 -4.14 15.38 ·3.67 '0.42 -2.14 -1.32 -3.54 -3.45 -1.41
1 H H e 101 ~3.00 -5.U 27.03 '3.91 ~!).43 -2.31 -3.'19 ~6.10 -3.11 -2..03 T ti S e ti '2.70 -3.51 10.07 -2.~7 -0.43 -2.31 -1.82 ~1.32 ·2.96 -7.95 T H o e w -2.61 -3.60 11.26 '2.81 -Q.41 -2.18 -1.82 -2.02 -2.6; -6.84
$: i ti t A '2.86 -5.21 -9.lO '4.02 -n.42: -2.14 -3.30 1.80 -3.33 ·.29.la s L S M ti '2.68 ~3.55 4.73 -3.32 ·0.43 -2.47 -3.79 -0.9& '2.85 -15.34 S l. S t w -2.86 -4.80 -3.54 -3.15 -0.43 -2.74 -3.79 -4.15 -3_31 -29.37 $: 1. o e w -1.83 -4.76 -10.29 -3.75 -0.40 -2.7.5 -"2.80 ·4.71 -0.S4 -31.82 $: M H M A -1.83 -4.24 '9.64- -3.77 -0.40 -2.27 -3.30 1.05 -2.54 ~2S.25
SHSMA -2.10 '3.44 '8.03 '2.75 -0.42 -2.39 -3.30 1.23 ·2.18 -23.31 SM!)MA -2.15 -5.15 -10.12 ~3.97 -0.42: -2.80 -3.30 -5.64 -'.40 -35.57 s M $: lit ti -2.95 -4.90 '4.18 ~3.61 -0.43 -2.78 -3.7'9 26.25 '3.71 -0.72 SMDM\t ~2.99 -5.30 -10.63 '3.84 -0.43 ~2.73 -3.79 -6.10 -3.69 -39.50 $ /11 S e w -0.22 -1.99 '9.69 '2.09 -0.42 -VS2 '2.80 -2.55 3.40 -15.91 SHnc\oI -0.41 '5.00 ·'O.~ -4.07 -0.41 ''2.74 -2.80 ~3.84 3.31 '26,7'0
1
Ranking 01 .. eh dltS.l by ctit*$lorin. .". ttaas producto Growth lIural • %CIAr out.ide
Potenti.l potffltíal equity 3.1 3.2 3.3 COLntr. c_. BruH
t 1 l ti M A 6 25 io4 " l " ,
" • , T L S " A 1 13 ]S 3 1 t 1 31 2
3 T l o M. 1. " .. l. 11 • 14 .. 10 , T 1. H e A 26 .... " 41 • 22 " 41 26 , TI.OCA 1 " 41 t. 2 3 • 14 • 6 1 1.. o e A • ,. 42 ,. , • lO
" " 1 1 LflMIJ 22 " ,. 11 lS 11 ,. 3l 15
• 11.$"" 3 , " t 1 , 2 " 1
• T lOMII 4 1 15 2 13 2 11 26 3 10 T l ti t w ,. 3S 13 31 ,. 11 ,. 30 16 11 TlSCII ., , 27 • ,. " • 2S , " Tloew , • 13 • , 7 ., 13 , " TMHM:A 21 10 t. tz 11 ,. 7 .. '" " T M S M A t3 11 2l 7 t2 13 3 " t3
1S 1fi11HfA 2l 11 12 20 22 t. ,. " " 16 T M H CA t. ,. 16 " " 22 " , ,.
17 T fiI $ t A , , 3l , • 5 4 , " " T M o C A 12 15 "
,. • 14 15 ,. " ,. 1MX/lltl 11 21 1 22 16 21 2' 22 13
2U TJI!SMtl 17 , ., • 2l 15 ., 17 " " T M o M'" 14 7 " • 28 • 21 • " " T JI! H e w 17 34 17 4. 37 33 30 , lO
" TMsell 20 • " " 21 ,. 11 7 17
" T M o e lrI 15 14 2, 13 ,. " 22 21 12
Z5 1 H K M A 27 22 26 25 31 " 34 ,. 3l 26 T K S /11 A 34 3' 21 " 26 " 25 " 31
" 1 If ¡)Ji'" 44 lB , 16 4. " 33 3. " " TI1MCA 11 • 3tI 15 ,. ,. 20 • " " TlIstA ,. 23 2. "
,. 2l " 2l " 30 T ti o C A " 27 5 26 ,. .. , . 36 " 31 THH/IItl 45 40 4 " 47 44 40 47 44
" T ti S /11 W 38 26 , 30 42 '7 27 , ,. 33 r 11 O M'tJ " 36 6 " 38 43 28 11 " 34 T M H t w 47 .. t 44 .... 47 41 .. .. 3S T H S e w 3S " 10 "
,. .. 31 ,. 34 ,. THDCW 33 31 • .. 27 Z5 3Z 33 28 42 Sl.DtA 41 '5 48 .. 35 42 42 11 " 44 s l $: fII W 36 30 " 33 44 3Z .. 27 31
47 S L S t w 40 19 as 37 41 .. 44 .., 19
48 SLOCIJ 24 37 56 38 25 36 lS " ,. " S M H M A 25 13 '2 39 24 26 41 • 30
" S M S "A 28 28 34 27 34 30 38 " Z5 S. SM!)"A. 30 44 59 45 " 46 39 44 22 ,. SMSM\! .... 41 2S 34 46 " 43 1 47
57 SJI!I)"W 46 47 57 42 .. 38 .. ., 45
5' S JI S e W " " " 2l 33 34 36 34 7
60 s H ti e w ,. 42 60 47 29 19 31 ,. a
DA'I:A ANALYSIS FOR DECISION IIAlUNG IN NATURAL ltESOllRCE HANAGEHElIT
FOR SUSTAINAIlLE AGRICULl'llltE
Juruo 1990
P. ,Jones and D. Robison
Agroecological Seudies Unit - ClAT
DESGRIPTIONS OF ENVIRONHENTAL REGlONS CHOSEN FOR FURTHER STUDY.
GlASS 2.
AGID LOI/LII:!ID TROPIeS SEASaNA!. HARlTIHE.
This class is heterogeneous. It include$ highly populated areas of
coastal Brasil under sugar eane and cacao, some similar arcas in the
Caribbean and Central Amariea. Larga are as of semi-evergreen seasonal
forest in Arasil, Peru, Colombia, Bolivia and Central American
councries. Ie a150 includes the savannas of che Colombian Llanos sud in
Venezuela, and areas of the northern Cerrados.
CIASS 5.
AGID LOI/LII:!ID TROPIes SEASONA!. CONTINENTAL
This clasa 15 the continental counterpart or class 2. Much oí che area
1$ seasanal fores t al though soma areas are lowland savannas. Large
extents are inacce.ssible sud lightly populated.
GlASS 8.
GOOn SOIL ID1lLAliD TROl'ICS SEASONAL MAlUTIME.
lncludes heavily populated coastal areas throughout che regions. apart
fraro Peru, An anomaly in this reglan as mapped i.s that it includes
poorly drained areas in Bolivia, Arauca Colombia and soma regions of the
Amazon basin,
2
ClASS 9.
GOOD SOIL lDYLAND TRopres SEASONAU.Y DRY HARITIHE.
Tbis class includes heavily populated coastal areas Di N. E. Brazil,
Venezuela, Colombia, Ecuador, Costa Ri __ cl. •• d l'Iexico. It contains lower
populated areas oi the Yuca tan , Honduras and Bolivia.
important class fer Mexico.
Perhaps mast
Much Di the are a 1s hilly, contains rnuch cotton and various
annual crops. Also an important sugar cane regian.
CLASS 11.
GOOD SOIL LOlJLAND TROpreS SEASONAL CONTINENTAL
The continental counterpart of Class 8. Although sorne are as are truly
good s011s, highly productive and well populated, signifícant areas oi
this class are remo te poorly decimal areas in che continental interior.
CLASS 17.
ACIO !lEDIDI! ALTlTUDE moPICS SUSONAL CONTINENTAL.
Also a highly heterogeneous class but closely al1ied to the coffee
areas. These are the poorer coffee areas throughout Central America and
the Andes. Large areas in Brasil include the high cerrados around
Brasilia and CPAC but also the more broken terrain of the coffee areas
to the south. Apart from the savannas of Roraima and Guyana and the
northern extent of the cerrados all these areas are moderately to highly
populated.
CLASS 20.
HID ALTlTUDE GOOD SOIL SUSONAL mOPICS HARITIME.
Hill slope areas with high population -coffee zones throughout Central
America and the Northern Andes. The good 5011 companion to Class 17.
Also good soil areas in coastal Brasil.
DATA ANALYSIS FOR DECISION MAKING IN NATURAL RESOURCE
IlANAGEKENT POR SUSTAIliABLE AGRICllLTIlRE
CIlARACTERlZATION OF LANOOSE IIITIlIN EAGH OIASS
I'I!ASE II
13 August 1990
P. Jones, D. Robison, S. Carter
Agroecological Studies Unlt-CIAr
The selection of environmental classes within which te concentrate
does not. suffice to charac.terize and identify resea:rchable problema.
Problems with the use of land resources depend as much en che natura of
the landuse as on che nature of ~he resources. The purpose of Phase 11,
cherefore, \las ta a.ssess che actual landuse in the selected environ~
mental elasses co identify and organiza the nature of problems resulting
troro the respective landuses.
Tbe approach used was to consider each contiguous area of a
selected environmental cIasa (referred to as a subzone) and determine a
numbe-:: of variables relacing to its actual landuse. Figure n.l is an
example of the worksheec thac was filled for each subzone ovar 600 km2.
Thac cutoff size reduced che numbe.r of subzones from over 500 to jase
over 300, yet accounted for over 98% nf the area. The actual variables
were chosen in conjunction with che economists.
Using maps censuses, atlases and reports, simple variables were
noted for so11, topography. clim..ate I natural vegetation, actual use,
principal crops, principal farming systems. populacion density, urban
dependence on agriculture, land distribution, l of are a readily
accessible -::0 transport and relative distance to market.
absorbed three people working full time tor three months.
This work
PAIS: TITULO:
DESCRIPCION
TOPOGRAFIA < 8
PROFUNDIDAD : DRENAJE: PROBo QUIMICA: PROBo FISICA:
BIMODAL:
VEGETACION NAT. RIEGO % : PERENNE : BOSQUE MAN.
ANUALES (en orden):
PERENNE (en orden):
1.-
2. -
3. -
4. -
DEN. POB.: LANDLESS: X EXP. < 10 Ha.: ACCESO:
HOJA ONC: SUBZONA: AREA :
8 < 30 > 30
SUELOS
TEXTURA
CLIMA
MESES > 200 mm. :
USO DE LA TIERRA
SISTEMAS
% : ANUALES PASTURAS X RASTROJO LARGO
Pl:
P2:
P3:
P4:
DEP. URB.: IPCR: X AREA < 10 Ha.: AISLAMIENTO
FIGURE l. SURVEY YORKSHEET
TABU 6. Patrones de uso de 1a tierra identificados
Ganaderia Ext,. Cultivos Disc., Bosque Natural
Ganadería Extensiva
Ganaderia Extensiva
Ganadería Extensiva
Ganadería Extensiva
Culto Mee. - Cultivos DiscontinuQs
Cultivos Anuales Meeh - SQsque Nat.
oosque Natural
Cultivo Discontinuo Tradicional
Ganadería en Pendien=e - Café ~ Frutales, Maíz, Frijol
Ganaderia en Pendiente, Caré. Cultivos Discontinuos
Frutales - Ganaderia Pequefta Escala ~ Cultivo Disc.
Caña Intensiva - Ganadería Intensiva - CultivQ Mec.
Caf.a y Cultivo Pequeña Escala
Ganaderia Pequena Escala - Cultivo Disc., Frutales
Cultivos Intensivos con Riego
Cultivos Intensivos con Riego
Ganadería Extensiva
Cultivos Mixtos Mee.
Ganaderia Extensiva. Cultivos DiseontiñUQs, Colonización
Cultivos Mecanizados Escala Media ~ Ganadería Med.
CE-CO-EN
CE-CK-CD
GE-CII-BN
CE-BN
CE-GD
GP-CA-Fl(
CP-CA-CO
FR-GP-CD
Cl-Cl-CM
CN-CP
GP~CD·FR
CIR-GE
CIR-CM
CE-CD-CC
CMM-CII
Ganaderia Mixta-Arroz Secano Mecanizado-Otros cultivos Mec. GMNAS-MM
Cultivos Disc., Ganadería en Pequeña e'seala, colonización
Ganaderia Extensiva en Tierra Inundada
Cultivos Cisc, . Bosque Manejada - Ganad. Peq. Escala
Ganadería Pequeña Escala, Culto Oisc., Banano
Goma (Caucho) y Castaño extensiva
Cultivo Discontinuo - Ganadería Pequeña Escala
Sistema Fluvial selvática en Tierra Firme
Sistema Fluvial selvática en Várzea
Pastoreo Extensivo de Caprinos
Ganaderia Extensiva - Palma Africana
Café y Cultivas Mecanizada. Ganadería Intensiva
CO-CP
GEl
CD-BH-CP
GP-CD-B
GO-CA
CD-GP
FrF
FV
CP
CE-PA
CAM-Cl-CM
*
* El orden de las abreviaciones no siempre representa la predominancia relativa entre los sistemas de un patrón.
Parallel to this process Jenny Gaona and Argemiro Monsalve "'ere
conductlng interviews wit:h visitors to CIAT from different countries,
anc obtaining recent, first hand information abóut as many subzanes as
pos$ible.
Once these variables had been determined for the 300 subzones, they
were usad ta determine systems, and the combinatian of these ta
determine land use patterns. lt 1s important ta nóte that vir~lly al1
of the subzones had al: hast two modal landuses systems. that is.
¿ifferent systerns practiced by different people within the same area ego
ex~ensive cattle ranching and sh1fting cultivation. Table 6. show$ all
of the landuse patterns described. regardless oi environmental class.
Vegetation
Tabla f, helps il1ustrate t:he limitations of using original
vegetation alone te separa te eeozones. Approximately the sama
percentages of a.reas formerly under forese and savanna are now under
cropping or pasture. !here is as much managed forest in former savanna
areas as in former forest areas. While each environmental cla.6f.S is
mai:l1y: one vegetation type or the other, we found instances of saVanna
ano forast in eacn of the 7 classes that we eonsider~d.
Each oi the environmental cluses has an area of steep dopes
conseituting "ladera". Each e la.ss had areas wi th ex tens i ve use ,¡ind
o:chers with intensive use. However in the process
describing each area, we quickly came te realize
oi individually
that there are
repeating ?atterns of land use with common problems and pecential .as
well as similar environments. The process below is attempt to organize
these repeacing pattarns iuto a structure that allows for simplification
while retaining che necessary complexity.
TABLE 7, Vegetation in the selected classes
Original E:d$ting AeCt:S$lbt. Mea uncIe!" AnnJal . ,.. f'erut 1366839 574009.9 915543.5
Sa\'/IlMa 804689 415513.1 583551
I,Jnctassif. Z93ó6l 1467'90.7 240436
Total 2465191 113717'. 1739531.
LANn USE PATTERN GROUPING
grazing
358376.1
431644.0
135456.8
eropp •
143767.6
68113.37
26861.36
84159.48
10384.96
19310.44
Mechar.!,.
61572(1.8
42~67.5
65907.8
Thé land use pacterns were assigned to each of the 300 subz:ones
along wlth the envlronment elass. When serted by predominant patterns a
series of groupings appeared whieh seerned te be logica1. 'l'hese were
inspected and clustered accarding ta a consensus Qf subjective éscimates
of similarity among chose working in the unit. Sines much of the
infonuAcion was ñon numeric and nnt arde red this was considet'ed Itlore
appropriace chan a numeric clustering algor1thm. Figs. 2 and 3 show che
areas and population respectively for these land use pat.tern groups
within the six environmental classes selected in Phase l.
These follows a selection of descriptions of the main clusters.
._[-1'---UNU5EO fORES
RU BBER· NlJTS
T lANOS
fLUV1AL!. VAR SEA SYSTEMS
E POOR lANDS E: GOOOlANDS
lNTENSIVE CAN INTENSIVE CAN INTENSIVE IRR: IGATION
NIZED COffEE. AREAS BRASIL MECHA NlECHANIZED M EDtUM SCAlE
PE PASTUAES MECH CROPPIN'" CERRADOS TY PODA LOWlAN O PASTURES MECH CRQPPING
ENSIVE GRAZING POOA SQllS '---lOWlANO EXT
GOODLOWLAN O PASTURES MECH CROPPING
paORl y DRAIN
GOQDlOWLAN HIGHlAND rAS
eo PASTURES
O PASTURES ALONE TURES AlONE
LOWLANQ EXT ENS1VE GRAZING POOA SOllS
O PASTURES MANUAL CROPPING POOA LOWlAN GOQDLOWlAN
OAYLOWLANO DRYlOWlAND GOAT GRAZIN G
O PASTURES MANUAL CROPPING
PA$TURéS MAN/MECH CROPS PASTURES MANUAL CROPPING
lE COFFEE POOR SOIl r-- LADERAS CATT
'-- LADERA~ GR A21NG SHIFT CUlT PODA SOll
lE COFFEE GOOD SOll ~ lA PERAS CATT
LADERAS GR AZING SHlfT cun GOOD SOll
LDWLANDCA TILE COFFEE
LT1VATION SHIFTING CU
SMALl SCAlE CANE Sr MANUAL CULTlVATION
2
n.o"
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Environment 'Class
5 8 9 1 1 17 20 ! .~
6.45 4.05
063 .- 5.56 12.42 0.94
2.IL!l .. 10017 . .-46. 5 ~2Q . ?Ofl Rn 138.90
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_.547 064 2'9.99
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R 4~ 49.04
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14.12_ ,871 1 R 59 .~
4.83 4.57' 0.26
6.16 17,02 8.45 10,67
UNUS ED fORES
RUBBER. NUTS
T LANOS
flUVIAL & VAR SEA SYSTEMS
E POOR LANDS INTENSIVE CAN II'JTENSIVE CAN JNTENsrVE IRR
E GODO LANDS lGATION
NIZED COFFH AREAS BRASIL MECHA MECHANtZ.ED M EDIUM SCA!.':
PE PASTURES MECH CROPPING CERRADOS Ty POOR LOWlAN
LOWlAfIID EXT
aOODLOWLAN
POQRl y ORAIN
GODO lOWLAN ~HGHLAND PAS
o PA$TURES MECH CRQPPtNG
ENSIVE GRÁZING PODA SOlt.S
o PASlu~Es MECH CROPPINC
ED PASTURES
D PASTuRES ALONE TURES ALONE
ENSIVE GAAZING POOR SOILS LOWLANO EXT
POORLOWlAN GOOO LOWLAN
o PASTURES MANUAL CROPP1NG 9 PASTURES MANUAL CROPPING
DR)' 1.0WtAND DRY LOWLANO GOATGRAZIN
PASTURES MAN/MECH CAOPS PASTUAES MANúAL CROPf>ING
G -__ r- LADERAS CATT
.J~ LADERAS ORA LE COFFEE POOR SOIl
ZING. SHlFT CULT POOR 50ll
I r--- LAD~RAS CATT
~ LAOERAl? ORA
lE COFFEE GOOO SOll
ZING SHIFT CULT GOOo SOIL
lOWLAND CAn LE COFfEE
TIVATION . ~ -~
~~E SHIFTING CUL
SMALl SCALE
LOWLAND GR
CANE & MANuAlCULTIVATIQN
AZING, SHIFT CULT ON SlOPE
2 5 ~
1.68. 0.17
2.58 1 ~ R.
6.11 0.18 ~~
7 Sl
317 4.0~
11.27 29.22 3~35 1.06
4 49 1 60
3~35 1 ~O6
174' "1 21:.
~
~
205
0,26
1 ~ 11 2~92
~8 9 11 17 20
~--
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1.62 1.77 ~
~ __ O_.4i?~
15.57 534 ", .73 ~ ~
1.27 o~ 4 () 72
n?3 1973 1.24 O
31 ü7
~~
339 2. '10
0.11 8,42 ,~ ".
() 54 0.35 (.L52
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4.98 1.73
" 1 n 079 13.92
4 4~ ~~
, n?
nno ___ ,L78 0.22
- 3át 2~89
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0.15 1~62 O~17
084 0.56 0.13 ~~-
O~05 1A7 0.2.3 OA2 O~26
0.26 1.62 ~
-~-
cu.sS 8 AND 9. IlITENSlVE CAllE, IlECHANIZED CULTIVATION,
TItase are as are charact:erised by intensiva estate managed sugar
cane, larga farm grazing of eultivated or induced pastures and
mechanized cultivat10n af sorghom soybean, cottan and often irrigated
rice. A small farm sector generally conCentrates on fruit and
horticultura! products. 'rohacen in soma areas along with heans, Olaize
and some cassava. Often irrigated, the clima tic difference between the
dry class 9 and seasonally wet elass 8 15 diminished.
50i15 are good and topography flat and easily mechanizable. There
i5 litcle or no remaining natural vesetation except: in placas where this
vas a nativa grassland suitable for grazing, Fallowing:'5 rarely
. practicad,
GrOW'th potencial is low in 1:érnts af area expansion, there being
little land unused. Movement to intensified meehanized cult:ívation may
diminish the importance oE grazing. The small farm sector may aCcount
for up to 80 percent of the rural population but only about 5-10 percent
of the land.
Increased profitability of broad scale mechanized crops might lead
Ca Hintensificat10n n and absorption of small farmer arcas, but this is
less likely than in sorne other areas becsuse the lat~er sector
concentrates on higher value erops for che urban markets.
Small farro. sector may prQvide labour for the astste and larger
farms but this 1s also supplied from nearly urban populations.
Problems
l. Erosion risk is~generally low but compaction by heavy machinery rnay
occur in some areas.
2. lr."hile these areas are not the typical arid irrigation anss, salt
buildup due ta poor irrigation practices ls a risk in many places,
3. Excessive use of pesticides and herbicides occurs frequent1y on the
commercial cropplng lands especially on rice, cotton and soybeans .
Spillover
Shift from grazing te cultivation w1l1 push cattle ta less easily
managed areas.
LOIILAND EXTENSIVE GRAZING POOR SOILS
CL\SSES 2 AND S (CARIl<AGUA)
These areas a~e found in the altillanura of Colombia, in ~exico snd
Venez.uela and have ao accessible area of 4.41 Mha. 50il$ are highly
acid and natural vegstatlon is savanna and semievergreen foresto
Topography 1s flac with only 5-20% on slapes from 8 to 30 pereent.
The land use pattern 15 differentiated from a further 29.2 milIion
hectares of Class 2 snd 5 savannas by having insignificanc cultivation
either perennia! or annual, manual or meehanized.
Populat:ion ls lo'W and average farm. size ls almost 1000 ha but
decreasing, !he principal production system i5 presently cowlcalf
operation on oatuve pastures.
isolatlon 15 not extreme.
Markets are relatively distant, but
GrótJth potent:ial 15 high far acid tolerant crops on mechanizable
land.
Problems
l. Erosion is little risk under native pasture but could become severa
on even moderate slapes under inappropriate cultivation.
2. Dastruction of the gallery foresto
Spillover
Intensificacion may increase the dernand for rural labour or enhance
che reduetion oí farm size.
Technology developed here should be applicable to toe Class 2 and 5
poor lowland pastures where mechanlz:ed cropping alre41dy exists. However
it may al50 be feasible to use in the cleared forast areas where large
numbers of SUlall farmers at present using manual methods might be
prejudiced, possibly increasing deforestation.
CLASS 2 AIID 5. POOR LOlIlAND PASTlliUlS. MANl1AL CROPPING
!bis ís a ver:y widespread frontier area. of 44.7 milItan hectares.
tt has varying degrees of a.ccess but generally moderate to high distance
to markets.
Land and income distribution are highly skewed. An average of 51%
of the farmers haya les$ Chan lOha but control a.n average less chan lOX
oí the land,
Natural vegetation
completely disappeared,
is semievergreen foresto
but overa11 about 40%
In some cases this has
oí che original forest
remains, !bis is usually located on che steep and inaccessible lands,
About 4% of the land is under parannia! crops lU in annual
cropping and 30% under extensiva grazing. In some ateas up ta 30% is
under bush fallow. Topography i5 heterogeneous but over half the area
is flae and inherently mechanizab1e. One third is undulating and the
remainder mountainous.
Population density is 10w to medium with a few areas of high
popu1ation in coascal Brasil and teh Caribbean,
30% to 70% of farmers have bet::ween 1 to 10 hec"táres, Access is
moderate ta good, with moderace distance to markets,
Problems
Most are as show a marked contrast between small farmers practising
shifting cultivation or long fa11owing, and extensive graziers.
Competition for land is reducing fa110w periods and inducing sma11
farmers te extend the forest clearance.
Soi1 depletion is a problem where fallow periods are cut due ta
land shortage,
lnsecure tenure for smallholders.
Sp1110ver
It may be that technologr developed for the lowland savannaS might
be applicable by the larger landowness. although they are not genera.lly
at present persueing mucb mechanized cropping. This would increase
competition for laud, and result is serious disbenefits for small
holders.
lIELL I/ATEREI) HID ALTITlIDE HIUSlDES
Classes 17 and 20
Compri.zes:
Laderas Cattls Coffee ¡toar Soil 3,02 !!ha
Ladera.s Cattle Coffee Good SoU 3,52 !!ha
H1gb Grazing Shift.. Culto Poor son 7,01 !!ha
High Crazing Shift, Culto Good So11 2,90 !!ha
Total 15,43
Throughout Central America the Caribbean and the Andes. Also
includes areas from Classes 14 and 23 not ana.lysed in this study.
Even at this level of classificacion these areas are highly
he'::erogeneous. Natural vegetation i5 mostly seasonal forest although in
soma cases humid or pre~montane forest, A small proportion, about 10%,
of this remains,
Access is generally good but least in che shifting cultivatian poor
5011 areas. Population Ls highest in the coffes areas and quite low in
the non coffee poor so11 regian. Land distribution i5 uniformly skewed
with approximately 80% of che farmeTs holding roughly 20: nf the land.
Iaolatian i5 generally low ta moderaCe a1though poor mountain Toads give
long travel times in sorne areaa.
Perennial eraps aceount tor up to 30% of the area, even in -:he
better non ceffee areas, Annual crops, beans maize eassava etc. are
groWlt on 5% ta 20% and between 20% to 60% is in pasturas. Bush fallow
aCCQunts for the remaining lands and may be frem 10% te 30% depending on
the atea,
Approximately 50% ef the area can be classed as rolling wit::h up to
40-50% steep nevercheless there is generally aboue 10% óf che area which
is flato
Problems
l. Erosion i8 a serious problem almost everywhere due to:
a) Overgrazing on steep pastures
b) Fire fallQw elear.nce
e) Poorly managed cultivation
d) In some cases poorly managed coffee.
2. Pesticide overuse ls prevalent in the coffee crop,
3, Although most oí the remaining forest is on steep lanos, there ia
still pressure for feIling.
4, Coffee washings are a frequent pollutant of streAma and rivers.
EXTENSIVE GRAZING AND SMALL-SCALE MANUAL CULTIVATlON,
IN TItE ORY. LO\o'l..AND AREAS OF NON-ACID SOIt..s
Glass 9
'Chis land-use pattern occupies about 14 millian hectares, mose of
which is accessible. The type lncludes sn important portion of che
Sertao in N,E. Brazil, che middle Sinú on Colombi's north coast, and che
Acapulco and Cancún areas of Mexico. The rural population density is
moderate tn high, and the total rural population ls estlmated ae
2,700,000.
Between 30 and 50 pereene of farms are leSs than 10 ha. aua control
les$ thao five pereeut of che land.
The natural vege.tation, scrub, dry forest and 'Aooded savanna, is
extant in al'proximately half on the area.
Agricultural lana use 1s dominated by pasturas, aboue 30~ of the
total atea, .'lOO bush fallow" The: laceer varies in impQt'cance, in sorne
pLaces ie reaches 40% of che acea. Annual crops accupy about ten
parcenc af land, and perennial crops are generally absent. Exceptions
tu the lattar are found in parts of N.E. Brasil, where cashews and tree
catton can occupy upto 1S1 uf the land.
Topography is predominantly flat (70X) wi¡;h the remainder mostly
rolling.
PrQblellí$
P~oblems associated wich the area's climata are important, that is.
the unreliability of raínfall 3nd tisk af drought. These affect humans.
crops and animals.
Adaptation te droughr: i5 most difficult for sma11holders who reIy
nn annual crops rather than axcensive grazing. Declining so11 fertility
is a significant prob1em fQr many of these people, due ta ovetcultiva
tion,
EXrENSIVE "ASTURES ANl) SMALL-SCALE MANUAL CULTIVATION
ON NON-ACID SOII.s 111 TIlE SEASONAL LOIIl1INI)S
Class 8 <lnd 11
!bis type occupies about 6.7 million hectares, in northern
Colombia, Venezuela, Guatemala. Belize, Mexico, Paraguay and Brazil (the
litoral in Ceará). !ha natural vegetation is seasonal and humid forese , on average half cf the ares retains this caver. Land holding patterns
vary greatly, Ihese areas are not densely populated. although tne total
rural populationis around two millian. Access varies a great deal,
A small percentage of che land, less ¡;:han five percent, ls under
pere~nials, and annual erops caver 5~40X, Pasturas covar about 40% of
-che area; che proporcion r1$es to 70X in some placas. Bush fallow is
unimportant.
Fort:y to ninety percent of che area has flote topography. with ten
ta fífty percent rolling. Steep topography 1s generally absent, and
does not usually e~ceed 30% of these regions where it is fauud.
Problems
Forest clearance is an important aspect of the agricultural
dynamics of ehese areaS, Frequently land is cleared by colonists and
smallholders, only for these to be displaced soon after by ranching.
Concentration of land ownership 1s parcicularly notable in accessible
areas and where the qualicy of land is particularly good.
As a result of insecura tenuta and land concentration. fragmenta
tíen and social conflice affect sedentary agriculture in numerous ways.
Many farms are too small to permit sustainable systems to be
by tlJ.eir owners. and so11 degradation ls to be expected.
instability of thesé areas prevents consensual resource
implemented
The social
management
amQngst al1 land users. Thi~ a1so contributes to inefficient, absentees
management of pastures. with the emphasis on area rather than pasture
and animal quality.
Like most new or recent frontier areas, social infrastruct"re
(health care, education. roads) 1s often absent.
CLASS 2 ANO 5. l'OOR LOl/lANIl l'ASTtlRES HECHANIZED CRílPPING.
SOKE KANUAL CRílPS
A large aTe oomprising 40.5 mUllon hec:tares in Brasil. Colombia,
Panama, Mexico and Paraguay, 29.2 militan hectares of this are lowland
savannas environment.ally similar to che Altillanuras oí Colombia, the
rest 1s seasonal forest. Tbe reason for separate classification from
the Carilllagua type is the enstence of s ignficant areas of mechanized
cropping, sometimes up to 30% of the land area.
111e area accounts for a population of 2.7 million. Accass la
variable bu~ ovar half the area has 100% accessibility. lsolation from
markets is variable but mainly moderate. a few cases being highly
isalacad,
SOt te 90% of the aTea is still in natural vegecátion but where
this is Savanna ie is grazed, Virtu.ally no perennial crops are grown
but lit~le oi che land is left as fallow.
Tha propol.'cion of flat land is relatively low snd can reach 25%.
the rast 1s classed as rolling wt~h steep lands less than 51 of che
ares,
Op to 50% of Che farmera use 1esB than 8% of the land.
crops include upland rice, sorghum and soma soybeans.
Problems
1, Erosion. A maximum of a third of che land 15 suitable for
mechanized cropping snd small fa~er crops are often relegated to
slopping lands.
2. Compaction by heavy machinery.
3. So11 depletion - so11$ are poor and not suitable for continual
cropping.
CERRADOS TYPE PASTtlRES AND KECIIANlZED CROPPING
class 17
The area of 31 millian hectares 18 almast exclusively ln Brazi1.
Access 15 moderate and distance ta market high ta medlum.
Depending on the distance ta population cantars Che rural
population varies fram low ta medium. At one extreme these are
essentially no farmers .... ith 1ess than 10 ha. but in the S.E, up to 50%
of farmera do.
. General1y over SOX of che area ls still natural veget4tion ~hich ls
campo cerrado, cerradao and seasonal foresto Almost no perannial crops
or managed forese. On the average 13% the area ls under annual cropping
but the proportion is higher closer ta markets, just undar half the area
is declarad as pastm:e, as a significant proportion of che area 15 in
sorne farm oí natural foresto
Only 54% oi the total area 1s less than 8% and ful1y 13% is ovar
30%, or very steep lane,
Problems
Eros1on
Compaction
water talbe modification under cropping.
Class 9. FXTENSIVE PASTURES • .KEDIUM OR LARGE SCALE KECHANIZED
ANJ) SMAll SCALE !!ANUAL CROPPING. OH GOOD SOILS
IN TIre DRY lDllLANDS
!bis type envers some 5,1 million hectares. in N.R. Brazil and Hato
Grosso. the sabanas de Bolivar on Colombia's nQrth enasto and srosll
areas in Nicaragua and :Solivia. Together they have a moderately dense
rural population of about 1.500.000, Between thirty and seventy percent
of farms are smaller than 10 ha, and ac.count for no more than five
percent oí the land.
Natural vegetation. which ranges fraro wooded savanna and sertao te
seasenal forest, covers appproximately one quarter ef the total a.rea.
Perennial crops are unimportant. Annual crops account for five to ten
percent of the area. !he preportion Df the are a under pastures varies
from 30 to 70X. and fallow from 10 to 30%. Topography is moscly flat to
roll~ng. Most of the type is accessible, moderately isolated from urba~
marke~ centres,
Problems
Availability of water for crQPS and livest:ock is a significant
problem as is unreliabi11ty of rainf11 for upland cu1tivation,
Since well·wacered land i5 such a critical resource for agriculture
competition is important. Sinee che land-ho1ding pattern is often
extremely skewed, with larga landholders dominating well~watered
bottomlands. conflict ovar both land and water i5 Common.
Smallholdings are too small for tradicional fallow~basad systems tn
remain effective, shortened fallows hsve led to soi1 nutrient depletion.
50i1 erosion i5 common. boch for small~scale and mechanized
agricul ture.
Acces$ ta markets is usually most: difficult just as smallho1der
crops are being harveted, at the end of the rainy season. Since there
are few opportunities for employment during the ry season, labour
migration i5 high, Lábour shortages for land preparation, and a, high
incidence of fema,le-headed families often result from al1 roale seasanal
r..igration.
GEOGRAFHIC SlJRVllY OF PROlILI!IIS 1lI ACIUGULnntE
Parallel ta che characterization of environmental classes and
land~use clusters, che AESU has beeo conduc.ting a simple ~11rvAy about
problems and research experience in Agricultura in Latin Amarlea. This
vas done in anticipation that the resule of the Agroeeo~zones study
mlght imply activities chat CIAT has nut done in che pasto The goals
were ta find out what organizations in Latin America haya beeo doing.
research in natural resourCe aspects of agric.ulture and for how long.
!he survey a150 requested a listing of the five most serlous problems in
agriculture in the respective aTeas. and che five mos~ serious obstacles
that the organizations themselves encounter. Additional questions relate
to the organization' s opinion of CIAT' s work in the pasto and what
activi~y CIAT could emphasize in the future.
Finally. information was requested on the geographical area that
they cover in their work. rhe purpose is to be able to roap ann analyze
the diseribution of chis information aboue organizations. Analysis
should help, for example, to detect subjects which have received lietle
attention or geographic areas which lack investigation oí a certain
nacure.
INITIAL IlESULTS
To date over 450 organizat1ons have bean contactad, mainly froro two
lists of NGO's and ClAT's 13.000 strong: mailing l1st. Prelim1nary
analysis has been conducted on the first 91 responses that were
received. 27 are ONG's, 6 international organlzations and the rest state
research organizations.
Table 1 indica tes che researeh subj ects Chal: were specifieally
mencioned in the survey and the percentage of organizations that have
sorne experience. The subject Chat mast organizatioos have addressed is
tha evaluation af alternative erops: 60X of organization have worked
with them.. and 40% have more than five years of experience. Of the
subjects that we specified. the least studied were water rights and land
rights. A few organi::ations haya deeades of experienee. eg. Instituto
Agronómico Campinas (lAG) with 25 years of research in 0rosion control.
Table 2 lists additional research ehat organizations have ~eported.
and that they consider te be relevant tO natural resource use" Sorne
obvinus omissions tn our original list illustrate one of trade~off with
the survey. Tf we provide a survey whieh 15 too exhaustive.
TABLE 2 Additional rBsearch subjects rBported by the first 91
rE!spondants: .
Agroecologia y monitoramiento ambiental.
Organizaci4n Comunitaria.
Manejo de Pasturas.
Manejo de Animales Menores.
Manejo de Parcelas Familiares I Huertas. Leguminosas Comestibles.
Fruticultura General.
Procesos Agricolas (Post-cosecha).
Sanidad Vegetal.
Ganado Mayor.
Mejoramiento de Variedades.
Sistemas Agricolas de Producción.
Análisis de políticas agrícolas.
PROBI.EKS
Unlike: ehe research subjects. we decided to leave t:he systems
blank, so as to noe limit or gulde the listing Qf problems. Appendix 1
lists the 43 unique problems that have been identified in the 91 surveys
to date, Roughly speaking oí the 455 possible answers, chese have
broadly into 43 responses, snd mest oí them into 15 responses.
Tbe organizations have been classified as internacional, state and
now-government (NeO) regardlesB of organization type the most conunon
response is 1. Degradación de recursos naturales: erosión y perdida de
fertilidad. Howaver che naxe mest common problems idencified differ
considerably, State organizations identify 10$$65 ta insect and dlsease.
followed by inadecuace comme.rcialization, irrigation snd draiaage
?roblems and a lack of market for alternativa crops. NGO's by contrast
cice inadecuate use of cechnology. land tenura, unequal, distribucion of
resou~ces. inadecuate commercialization and irrigation / drainage
?t'oblems.
Asida from land degrada~iQn the only overall common tap próble~ Co
the three organizat:ion type is inadecuate conunercialization. !he
responses on cne hand shows tendenciés relaced to che technical appraach
of state research and socíally oriented ~GOrs. With more responses and
further analysis it showed be possible to ident:ify more common ground.
rt 1s a180 important to note thac while natural resources are identified
as the mast important problems, relatively little research has been done
on some aspects.
OBSTACLES FOR THE ORGANlZATIONS
Two problems are. ovenhelming favoritas: "Falta de recursos" is
top for internacional organization but seeond in NGOls. First tor ~GO's
is ~Falta de politicas y reglamentaciones adecuadas del gobierno~. This
is 2nd and 4th for che ocher organhation. International and state
organizations a c:oneern far "Problemas administrativos" while
state and NGO's share "Insuficiente coordinación entre organizaciones".
International and NGO's agree on ~Formación inadecuada y unilateral de
técnicas.
Appendix 11 lists al1 oí the unique answers on obstacles.
these have varying degrees of relevance ta natural resource USe .snd
varying significance to possible elA'!" SI activitie.s. However geograpnic
analysis should help to reinforce t,he most relevant areas of CIA!' s
current wQrk and possibly sugges~ news act.ivit.ies.
1 1
APPENDIX L Problems identified among the five mose importanc in each
araa.
1. Degradación de Recursos Naturales, Erosión y Pérdida de
Fertilidad.
2. Minifundio excesivo.
3. Pérdidas ocasionadas por plagas y enfermedades.
4. Uso Indiscriminado de Pesticidas. (Agroquimicos)
(Dependencia),
5. Comercialización Inadecuada.
6,
7,
Dtscribucion Inequitaciva de Recursos (Tenencia de
tierra) .
Pobreza. Marginalidad y Emigracion a las ciudades.
(Baja capacitación de los agricultores).
8. Políticas Gubernamentales Inadecuadas.
9. Carencia de Apoyo Adecuado al Pequeño Agricultor.
10. Uso Inadecuado de la Tierra.
11. Uso Inadecuado de Tecnología.
12. Falta de Organización Campesina. (Organización
ineficiente de productos utilizados para servicios y no
para producción).
13, Deforestación.
14. Problemas de Riego y Drenaje.
15. Uso de Tierra Marginal.
16. Monocultivo y Falta de Rotación de Cultivos.
17. Desconocimiento del Ecosistema de la Región
18. Cultivo de la Coca.
19. Falta de Mercados para Cultivos antiguos ó
alternativos.
20, Quemas.
21. Inseguridad.
22. Alcoholismo.
23. Falta de opciones de Agrolndustria para dar valor
agregado (Problemas post.cosecha).
)
24. Cambio y descuido de los sistemas eradicLonales.
25. Transferencia de tecnología inadecuada.
26. Deficiente Producción y USQ de Semillas.
27, Falta de Cobertura total de la Investigación
Agropecuaria.
28, Deficiente Manejo de Fertilización.
29. Mala calidad de los productos,
30. Agricultura totalmente Exportada (Enfoque de Exporte)
31. Ausencia de una Verdadera Cultura Forestal. (Poca
tradic10n en agricultura tropical).
32, Falta de Mecanización Adecuada ó falca mano de obra.
33. Falta y/o Deficiencias de couocimienco$ profesionales y
Básicos, Escasa educación de los agricultores,
34, En ganaderia baja productividad tanto por unidad animal
como por área.
35. Falta de opciones reales para diversificación.
36. Proolemas financieros. Tasas de incarás altas contra
nivel de rencabilidad casi inexistente, altos coscas de
producción, escasez de credito$,
37. Infraestructura deficiente.
38. ~cnopolio de recursos genéticos,
39. Altos precios de insumas,
40. Heterogeneidad geográfica, (Terrenos en ladera con
mayor ó menor grado de inclinación),
41. Necesidad del campesino de actuar a corto plazo.
42, Falta de germoplasma adaptada.
43, Animales destructote$ (Depredadores).
A1'PENDIX Ir. List of obstacles identified as among che fLve mese
important.
1. Falca de Financiamiento para Programas de Extensión
en Agricultura Ecológica.
2. Falea de Apoyo y Apat1a a la Investigación de la
Agricultura Ecológica.
3. Falca de e$pec~alización y metodQlag1a en Agricultura
Ecológica.
4. Formación Inadecuada y Unilateral da Técnicos.
5. Falta de Integración (!nvestigación, extensión,
créditO') .
6. Inhabilidad para Hacer el Seguimiento de 10$ proyectos
y las actividades Iniciadas,
7. Falta de Políticas y Reglamentaciones Adecuadas del
Gobierno.
8. Carencia de Tecnología que Combine Productividad y
Conservación del Medio.
9. Lenco proceso de Consolidación y Concietización de
Organizaciones campesinas. (Ausencia de concietización
adecuada de la problemática alimentaria
pt:oductiva.
nutricional y
10. Apatia por parte del Gobierno a diferentes Niveles.
11. Insuficiente Coordinación entre instituciones con:
l. Transferencia de Tecnologia.
2. Sistématización de experiencias,
3. Otorgaciones de fondo ó credito,
12. Crisis Económicas y Políticas del País,
13. Dependencia en Agroqu1micas.
14, Tenencia de la Tierra.
15. Falta de Recursos Económicos y Humanos, Po11ticas
Salariales e Infraestructura Propia. (Disponibilidad de
tierra en la Est. Exp.
16. Poca Instrucción o Conocimiento de los Agricultores con
Relación a Consecuencias Ecológicas o Económicas,
17, Inestabilidad y otros Problemas de Comercialización.
18. Inseguridad por Problemas de Orden Público.
19, Falta de Personal Técnico y Apoyo a la Investigación.
20. Problemas Administrativos,
21, Falta de Incentivos y Estimulos para Publicar
Resultados. (Falta en la Difusión de la Información).
22. Falta de Planificación Estratégica a largo plazo.
23. Centralizacion de la Investigación y Personal
Capacit::a<!o. Ubicación geográfica de la sede principal
Dispersión geográfica de los investigadores.
24. Dependencia Económica de Ayuda Excranjera.
25. Coca y Narcotráfico.
26, Dificul~ad de acceso e Infraestructura,
27. Falta de Mercado para Productos Alternativos.
28, Heterogeneidad Geográfica.
29. Perfil socioeconómico de los usuarios atendidos
(Demasiada pobreza),
30. Atomización de los usuarios en algunas zonas atendidas.
(Dispersión de productores).
31. Alto indice de analfabetismo,
32. Ausencia de una verdadera cultura forestal.
33. Concentración PQblacional a las ciudades.
-34. Falta de cobertura total de la Investigación
Agropecuaria.
35. Dificultad en medir el efecto e impacto de las acciones
efectuadas.
36. Uso inadecuado de semillas (poco resistentes a las
enfermedades) .
37. Minifundio.
Referencias de Documentos.
MINISTERIO DE HACIENDA. 1985. Anuario Estadistico del paraguay. 1984. Dirección General de Estadistica y Censos, Ministerio de Hacienda. Asunción, paraguay.
MINISTERIO DE AGRICULTURA Y GANAOERIA, 1985. cuario 1985~ Ministerio de Agricultura Asunción, Paraquay~
Censo Agropey Ganaderia¡
CARTER, S.E. 1986~ Cassava Micro-Regions in Parts af Eastern Paraguay. Aqroecological Studies Unit¡ CIAT, cali, Colombia.
REPUBLICA DEL ECUADOR. Instituto Nacional de Estadística y Censos. Ir Censo Agropecuario, 1974. Bolivar, Guayas, Les Rios¡ Manabi, Pichincha. Cuadros! 11, 19, 20, 23. INEC, 1979. (pichincha - 1977). QUito, Ecuador.
DIORN (1985). caracteristicas de los suelos de la República Dominicana. Secretaría de Estado de Agricultura. Oepto. de Inventario EValuación y Ordenamiento de Recursos Naturales. Santo Dominqo. 1985.
IBGE (1989) Producao da pecuaria Municipal. 1987. Fundacao Instituto Brasileiro de Geografia e Estatistica IECE. Río de Janeiro. 1989.
IBGE (1983) IX Recenseamento Geral de Brasil. 1980. Censo Agropecuario. Fundacao Instituto Brasileiro de Geografia e Estatistica - lBGE. Rio de Janeiro 1983.
IBGE (1989) Producao Agricola Municipal 1987. Fundacao Instituto Brasileiro de Geoqrafia e Estatistica - IBGE. Rio de Janeiro. 1989.
IBGE (1980) Divisao Territorial do Brasil. Fundacao Instituto Brasileiro de Geografia e Estatistica - IBGE. Río de Janeiro. 1980.
IBGE (1988) Annuario Estatastico do Brasil. 1987. Fundacao Instituto Brasileiro de Geografia e Estatistica. IBGE. Rio de Janeiro. 198a~
COCHRANE, T.T., Sanchez, LG.¡ de Azevedo LG., Porras, J.A. and Garver e.L. (19bS). Land in Tropical Amarica. Centro Internacional de Agricultural Tropical, Cal!, Colombia. 1985.
IBGE (1970). Oivisao do Brasil em Micro-Regioes Homogeneas 1965~ Fundacao Instituto Brasileiro de Geograf1a. Dept. de Geografia. Rio de Janeiro. 1970.
'1 ,
Oficina Nacional de Estadística. 1971. Sexto Censo Nacional Agropecuario de La República Dominicana (Segunda Edición) .
Centre d'Etudes de Geographie Tropicale. 1985. Atlas D'Haiti. (CEGET-CNRS) et Universite de Bordeaux. 146 p.
Ministry of Agriculture. 1987. Jamaica, Country Environmental Profile. Ministry of Agriculture, Natural Resources Conservation Division. Kingston Jamaica 1987.
CEE. 1985. Anuario Estadístico de cuba. Comité Estatal de Estadística, Cuba. 1985.
Anon. 1978. Belize. Cattle Census 1978. Department of Agriculture. Belice, 1978.
Anon. 1985. Potential crops for Belice. Ministry of Natural Resources. Agricultural Information Unit. Mimeo. Dec. 1985.
GARCIA P. 1983. Investors Guide in Agriculture. Agricultural Information Unit. Belmopan Belice. Aug. 1983.
JENKIN RN, Rose Innes R, Dunsmore JR, Walker SM, Bischall CJ and Briggs JS. (1976). The Agricultural Development Potential of the Belize Valley. Land Resource study 24. Land Resources Division MOD. Tolworth Tower Surbiton England 1976.
Anon. 1979. III Censo Nacional Agropecuario. 1979. Director General de Estadistica. Ministerio de Economía. Guatemala. Dic. 1982.
SPP. 1981. sintesis Geográfica Programación y Planeación.
de Jalisco. Secretaria México, D.F. 1981.
de
INEGI. 1988. Síntesis Geográfica, Nomenclator y Anexo Cartográfico del Estado de Veracruz. Instituto Nacional de Estadística e Informática. Aguascaliente, México.
SPP. 1982. Manual de Estadistica Básicas del Estado de Oaxaca. (3 volumenes). Secretaría de Programación y Presupuesto y el Gobierno de Estado de Oaxaca, Mexico.
SPP. 1981. Síntesis Geográfica de Nayorit. Secretaria de Programación y .l ...... dneación. México D. F. 1981.
IGAC. 1988. Suelos y Bosques de Colombia. Instituto Geográfico Agustín Codazzi. Bogotá, 1988.
VENEZUELA. Inventario Nacional de Recursos AID/EARI Atlas No.8. Engineer Agency far Resource Inventaries. Dept. of the Army. Washington, D.C. Jul. 1968.
TORRES, E~H., Granados, F.J., Mendez Acero J.A. 1977. Estudio agrológico detallado de la estación experimental de Bramen. FONIAP Dept. de Agrolegia. Maracay. 1977.
COPLANARH (1974) Inventario Nacional de Tierras. Región del Lago de Maracaibo. República de Venezuela. Ministerio de Agricultura y Cria. Caracas, 1974.
MAC (1981). Anuario Estadistico Agropecuario 1978. RepUblica de Venezuela. Ministerio de Agricultura y Cria. Driección General de Planificación de Sector Agricola. Dirección de Estadistica. Caracas, 1981.
ONERN. 1972. Inventario, evaluación e integración de los recursos naturales de la zona de los rios Inambari y Madre de dios. Oficina Nacional de EValuación de Recursos Naturales. Repüblica del Perú.
ONERN. 1968. Inventario, evaluación é integración de los recursos naturales de la zona del Rio Tambo - Gran Pajonal. Oficina Nacional de Evaluación de Recursos Naturales. República del Perú~
MDAjUSAID. 1985. Perfil de Area Distrito de los Santos. Volumen IV. Ministerio de Desarrollo Agropecuario, Dirección Nacional de Planificación Secteral. Panamá; Feb. 1985.
República de Panamá. 19a1a GUarto Censo Nacional Aqropecuarioa Volumen III. Características de las explotaciones agropecuarias. Dirección de Estadistica y Censo.
IGNTG. 1988~ Atlas Nacional de la República de ,Panamá. Instituto Geográfico Nacional "Tonuny Guardia".
BOLIVIA. INE. 1987. Ir Censo Nacional Agropecuario: Resultados provisionales. Instituto Nacional de Estadistica. Ministerio de Planeamiento y Coordinación. República de Bolivia. (7 volumenes).
INEC (1985) Anuario Estadistica de Nicaragua. 1985. Instituto Nacional de Estadísticas y Censos. Managua 1985.
OEA (1978) República de Nicaragua. Programa de Descentalización y Desarrollo de la Región del Pacifico~ Secretaria General de la'Organizaci6n de los Estados Americanos. Washington, D~C~ 1918.
Referencias de Mapas.
INSTITUTO GEOGRAFICO MILITAR. ~9S0. Paraguay. 1:1,000,000. 3a. Edición. IGM, Asunción, paraguay.
IGM. 1979. Mapa Nacional. Escala 1:200,000. Hoja SG21-3. San Estanislao IGM, Asunción, paraguay.
IGM. ~9g0. Mapa Nacional. Escala 1:200,000. Hoja SF21-15¡ Lima. IGM, Asunción, Paraguay.
CIAT. 1984. Paraguay. Región Este. Asociaciones Mayores de vegetación, areas intensamente cultivadas y pastos. Mapa no publicado, Unidad de Estudios Agroecológicos, CIAT, call, Colombia.
ECUADOR; Ministerio de Agricultura y Ganaderia, Programa Nacional de Regiona1ización Agraria (PROMAREG). (Mapas} Escala 1:200,000. Quito, Ecuador:
1980 1982 1984 1983 1983 1983 1984 1984 1983
Portoviejo. Bahía de Caráquez~ Quinindé. Santo Domingo. Quevedo. Muisne. Guayaquil. Babahoyo. Quito.
carta de Suelos Mapa morfo-pedológico# Mapa morfo-pedologico. Mapa morfo-pedológico. Mapa morfo-pedológico. Mapa morfo-pedológico. Mapa morfo-pedológico. Mapa morfo-pedológico. Mapa de aptitudes agrícolas.
BELIZE. Mapa Físico Politico, vias de comunicación y topografía. 1:250.000~ Transversal Mercator Cook Hammond and Hell London. Land and Survery Dept. Belize. 2 Hojas. ~9a5.
BRITISH HONDURAS. Provisional soil Map. 1:2S0.000 A.C.S. Wright and others. Base de datos de The British Honduras Survey, Forestry and Geological Depts. 1958.
BRITISH HONDURAS. Natural vegetation Map. 1:250.000 A.C.S. wright and others. Base de datos de The British. Honduras Survey. Forestry and Geoloqical Depts. 1958.
Mapa de Capacidad Productiva de la Tierra. 1:500.000 IGN, INAFOR f SGCNPE. Instituto Geografico Nacional de Guatemala. 4 Hojas. 1980.
Mapa de Zonas Nacional Militar.
de Vida a nivel de Reconocimiento. Instituto Forestal 1,600.000. Instituto Geográfico
Guatemala, C.A. 1983.
Mapa de CUencas de la RepUblica de Guatemala. Instituto Geografico Nacional. Guatemala, C.A~ 1978~
MEXICO. carta Edafolóqiea. 1:1.000.000. Lambert Conica Conforme. Secretaria de Programación y Presupuesto~ Dirección Genera de Geoqrafia del Territorio Nacional México. Hojas estatales~ S Hojas. 1981.
MEXICO. Carta Fisiográfica. 1:1.000.000. Lambert Cónica Conforme. Secretaria de Programación y Presupuesto. Dirección General de Geograf1a del Territorio Nacional. México. Hojas estales. S Hojas. 1981.
MEXICO. Carta Geológica. 1'1.000.000. Lambert Cónica Conforme. Secretaria de Programación y presupuesto. Dirección General de Geografia del Territorio Nacional. Mexico. Hojas estatales. a Hojas~ 1981.
MEXICO. carta Topográfica. 1:1.000.000. Lambert Cónica Conforme. Secretaria de Programación y presupuesto. Dirección General de Geoqrafia del Territorio Nacional. México. Hojas estatales. a Hojas. 1982.
Mapa de solos do Brasil. 1:5000.000. 19S1. Servicio Nacional de Levantamento e Concervacao de Solos. Río de Janeiro, Srasil.
projeto Radamhrasil. Mapa exploratorio de Solos. 1974-198 Folha l. Ministerio Dos Minas e Enerqia. Rio de Janeiro, Brasil.
Levantamento de Reconhecimento Dos Solos do Parana. 1:600,000. 1981. EMBRAPA, Servicio Nacional de Levantamento e Concervacao de Solo. Rio de Janeiro, Brasil.
World Atlas of Agriculture. 1'2,500,000. Instituto Geográfico de Agostini SpA. Novara. 1969.
Mapa de Unidades de Recursos para Planificación 1'250,000. Departamento de inventario, evaluación y ordenamiento de recursos naturales (Programa SIEDRA). Santo Domingo. 1980. -~
Projeto Radambrasil. Amazonia Legal 1:2,500,000. Ministerio das Minas e Energia. 1983. Brasil.
Operational Navigation Charts. 1'1,000,000 Oefence Mapping Aqeney. Aerospace centre sto Lois Missouri. Varios aheets and edition.
Soi1 Map of the World, Volume III, Mexico and Central Ameriea. 1'5,000,000. FAO¡UNESCO. paris. 1972.
So11 Map of the World. Volume IV. South Ameríca. FAOjUNESCO Paris. 1971.
Mapa Topo9ráf1co General, Santia90 NE19-l 1:250.000 Joint Operatlons Graphic proj Tranv. Mercator. Instituto Geografico Universitario, Santo Domingo. 1979.
Uso actual de la Tierra y tipos de Vegetación. República Oominicana 1:250.000 Proj* Tran. Mercator. Petar H. Freeman. OAS. Santo Domingo. 1966.
Distribución de la Población Urbana y Rural. Republica Dominicana 1:250,000. Proj. Transversa Mercator. Robert W. Fox OAS¡ Santo Domingo. 1966.
ICGC. 1978. Atlas de Cuba. Instituto Cubano de Geodesia y Cartografía. La Habana. 1978.
Academia de Ciencias. 1970. Atlas Nacional de Cuba. Academia de Ciencias de Cuba. Academia de ciencias de la URSS. La Habana 1970.
RepÚblica de Colombia. Mapa de Suelos 1:1,500.000. Instituto Geo9ráfico A9Ustin Cedazzi. B090tá, 1983.
Atlas Regional Andino. 1982. Instituto Geografico Agustin Codazzi. Bogotá. 19B2.
Atlas de Colombia. 1977. IGAC, Instituto Geográfico A9Ust1n Codazz!. Bogotá. 1977.
GRITA-TORSES. Estudio de aguas y tierras 1:100 1 000. Corporación de Los Andes. CIDIAT-ula. 1968.
Republica de Panamá. División Politico Administrtiva 1:500,000 Mercator Projection Heligraph. Copy Seccion de Cartografia. Direcci6n de Estadística y Censo. Panamá. 1970.
Mapa Pluvimétrico de Imágenes de Satélite 1:250,000. 1984. IFG. (Institute for Applied Geosciance, West Germany).
AMERICA DEL SUR. (Bolivia). 1:250.000. Serie H531. Institute GeQ9ráf1co Militar. República de Bolivia (Varia hojas).
Mapa de Cobertura y uso actual de la Tierra. Bolivia. 1:1,000,000. Programa de Satélite Tecno~6gico de Recursos Naturales. ERTS, Bolivia.
NICARAGUA - Uso de la Tierra. 1:1,000,000. Inventory Center. Corps. of Engineers 1965.
AID Resources Washington D.C.
NICARAGUA - Configuración de la superficie. 1:1,000,000. AID Résources Inventory cantar. Corps of Engineers WaShington D.C. 1965.
NICARAGUA - Vegetación. 1:1,000,000. ArO Resources Inventor¡ Center. Carpa of Engineers Washington D.C~ 1965.
NICARAGUA - Suelos. Center~ Carpos
Ingeniería. of Engineers
AID. Resources Inventory WaShington D.C. 1965.
NICARAGUA - Suelos - Agricolas. AID. Resources Inventory Cantero Corps of Enqineers, WaShington, o.c. 1965.
REPUBLICA DE NICARAGUA. Mapa de suelo de fases de subgrupos taxonómicos. 1:500,000. Proyecto CRlES. Ministerio de Agricultura y Ganaderia. Heliograph Map. Managua. 1978.
SELECTION OF AGROECOSYST!HS
DELlBERATIONS OF IJORKING GROUl' 4
18 Augus~ 1990
S ,Cartel.'
A, Aroas Evaluated
Within the envitonmental elasses selected by che Agroecological Studies
Unie and commodity economists, land use was found to be highly
patterned. A hierarchy of land use patterns was identified basad on che
scructure and intensity of associa.ted farming systems, Tlle patterns
were quite strongly concentrated in certain environmental classes.
Henceforth, we refar ta a particular comoination of land use pattern and
environmental claS$ as an agrQecosystem.
A considerable dacabase has been compiled as a result of che process of
agricultural characterization of énvironment classes, Ya Wére abla co
calculate che total ares. of each land use pattern within each class, and
to estimate rural population. '!'hese two variables gave us an initial
indication of the reLativa importance of the different agroecósyscems"
A nv.m.be-r of land use patterns, sorne spreading across different agro·
ecosystems, clearly stood out as worthy of further evaluation, whi:st
others could be rejected as insignificant. ~e have evaluated the most
impórtant land use patterns (and in cases where these were largely
confined to a single environmental elass, agl:oecosystem) as potential
areas for natural resouree management research ta focus, !hese were as
follows:
l. Areas oí intensive agriculture, partleularly sugar cane, moscly in
lowland areas and 00 non~ac1d soils,
2. Areas of mechan1zed erop produetion, particularly coífee. and found
~xclusively in &razil.
but some
population.
lowland
!bese were most extensive in the highlands,
systems contained a signific.antly large
2
3. Lowland and highland areas of extensive grazing and me.chanized
agricultura on acid $Oil5. !he Colombian Altillanura was a150
included in chis groQP. although meehanized erop produetion is not
yet important thére, !hese lana use patterns occupy seme 76
millien ha., and are by lar the mast areally extensiva of a11 those
identified. Tbey also have large absoluta populations, despite loy
overa11 densities.
4. Areas of extensive grazing and manual small holder cultivation on
acid soils. l'hese are also very larga (45 m ha.) with large
populations. !hay are mostly frantiar areas,
S. Areas of extensiva grazing and manual cultivation by smallholders
in the dry lowlands,
6. Highland srsas of extensiva grazíng, shifting or smallholder
culcivation. and perennial crops (notably coffee) on acid soils.
The ooly other significant land use patcerns not evaluated was thac
dominated by ex.tensive grazing on poorly drained pastures. This has a
smaller spacial ex:'ent. but possibly a higher total rural population.
than che highland catcle-coffee systams.
B. Selection Criteria and Proeedure
TQ evaluate the different land use pattern and environmental class
combinacións we devised a set of criteria, as follows:
Group 1 Economie potential
Market demand
Area or volume oí
total production
Oemand for agricultural production 15 significant.
Spatial extent, and¡or overall importance for
agricultural production 15 high.
lntensification
potential
Inf"rastructure
3
Existing production systems could be intensified
significantly.
Physical communicatlons and support service$ are
good.
Group 2 Resource potential
Productivity Index
Expansion cf
agricultural land
Natural vegetatian
Spillovers
Climatic and edaphic conditions are favourable
fer agriculture.
!here is scepe for area expansion of
a.griculture.
A strong value is attached ca conserving natural
vegetation and significant areas rémain.
Intervention will have a pasitive impac~ else
where, or non-intervention wil1 have a negative
impact elsewhere.
Group 3 Resource Problems
Ecological fragility:
Susta!nability of
existing agricultural
systems
Extent: of defaresta~
tian
Soil'degradatian
Tbe area le ecologieally fragile for
agriculture.
Existing syscems are not $ustainable.
Deforestaton ls a coneern over a large area.
S011 resourees are suffering s1gnlficant
degradation and/or eros ion.
Group 4 Equity
Rural poverty
Employment
opportunities
Food supply for the
urban urban poor
Land distribution
4
Tbere are a larga number of poor rural
inhabitants.
Significant employment opportunities can be
generated through agriculture.
'!he area supplies or could supply basie
fooostuffs ta urban areas.
Uneven land dist'tibution is a major source of
inequlty.
Group S Technological eonsiderations.
Lack of appropríate
or exogeneous technology: Appropriate t:echnology is noc currently
employed¡available.
Problems can be
addressed through
technology generation
Probability oi
generation
New technology can signifieantly contribute to
finding a soluciono
rt is likely ehs.t new technology can be
generated to salve identified problems.
Time frama N_v technology can be generated quickly.
Group 6 Institutional considerations.
Institutional
strength
CIAT's comparative
advaneage
Potential collabarators existo
Previous or current CIAr research can
contribute ta finding $olutions.
Internationality
Site availability
Each land
criterion,
u ••
on
pattern
rhe ag~oeéosy$tem is found in a rtumher of
eountries,
rt is feasible to begln research seo n aC eIA!
test sites or other known locations for a given
agroecosystém.
ot agroeéosystem was
point scala from -1
then
to
seo red, for each
+1.
!leutrality or irrelevance, Fo..: te.chnical considerations,
Zaro implied
if there was
no real lack of appropriate technology. giving a score of Al, then the
remaining criteria were automatically seo red as zero, sinea they became
irrelevant.
The scores for each group oí criteria ware then summed ta give an
overall seore, for che six agroeeosystems. rhe members of the te~ did
~his individually, and chan compared their scores. An average score was
then computad (Table 8). 1Jhere a sexong difference of opinion atose,
scores were discussed in detail for each cdterion to resolve :::he
disagreement, Mast diseussion centrad upon the extensiva grazing aud
smallholder systems of tha forast frontier. Here, intensificacion
pountial was considered as high relative to current 10'* levels. The
overall resource potential was reduced by a $core of one, since che
issue of conservation of natural vegetation vas eoverad under the
deforestacion crit:erion in che resource problems group. On equity,
rural poverty and ske"W'ed land distributions were considered important,
but: employment opportunities and food supply were both given a neucral
score, For technical considerations. the time frame was scored as zero,
giventhat tore could noC tdentify feasible interventlons at this stage.
To arrive at a final set of seores with which ta compare tne six agro~
ecosystems, we summed the scóres for each group of criteria. Ye
envisaged the need te apply different weights to cheSe scores. in
accordance with different views en the relative importance of gro .... th,
6
equity and sustainability as final seleetion critéria. To this end, ~e
grouped economie and resourc:e potential ca give a single indicator of
growt:h. Resource problems indicated che magnitude oí s~stainability as
sn issue in each agroecosystem, with equity untou.ched. As a fourth
factor, we combinad cechnological ano. institutional considerations to
indicate feasibiliey.
The results are givén in Tabla 9, which suggest where reSQu.rce manage~
mene will fíe best with CIAT's various goals. and where research 15 mast
feasible, Giving different welghes to ehe issues of growth. equity,
suscainability and feasibility WQuld have little affect on the ordering
of agroecosystems in Table 9. Only if we doubled the weights far equity
and sustainability. and halved those for growth and feasibility. would
the semi·arid pasture and manual cultivation syst:elUs ra.nk higher chan
the conglomerate af savanna agroecosystems, for example.
Table 8. Agroeeo.yste~ average icores tor grGuped evaluation eriteria.
--------------~------------------------------------------------------------------------------------------Agrou:osyst-em
1. lnten¡iv& ~¡ne. ete.
l. Pastures and .echani.ed
c:uitfvatlon
4. Paatura. and Manual
• ~ltlvatlon (for'.sr maroio)
6. Kiltstdc&: ps6ture., coffee.
Manual cultivation.
€collonli e Resour-ce
~otentjal Potcnt.
, - 1
,
,
, 1
R •• ouree Eql.lity
Pr¡)l'>lem.r,¡
1
,
o 1
4 ,
, ,
4 2
TeGhnieat lntitl.lt\ana\
consideratlan$ conslderations
2
•
3
•
3 ,
------------~--------------------------------------------------------------------------------------------
rable 9. Aaroa(:osystem sc;ore-s for growth, equity, sustainability and feas¡bllity.
fntenaivé (:an., etc.
2. "achani~~d coff.e, etc,
3. ~a.tur •• 6nd .echanlzed
cultivation
4. Pasturea and .anual
cultivatlon (foreat _.r,fft)
6. Hlltsidea: pasture" cofte.,
manual cultiv8Ii~n.
Growth
•
3
,
equlty $uatainability feu ¡bit tty
, ,
, ,
4
•
, 4 ,
Totat
,
2
"
" 5
15