I

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.

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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"

8.7<;

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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

'4 4. 4 . 405.76

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75.8' 39.35 .

_.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

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~

~

205

0,26

1 ~ 11 2~92

~8 9 11 17 20

~--

0.77

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

~ -~-~

4.98 1.73

" 1 n 079 13.92

4 4~ ~~

, n?

nno ___ ,L78 0.22

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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