Local and national concerns: criteria and indicators
“Best bet” Land-use Systems
Country reports
Alternatives To Slash-And-Burn In Indonesia
Unique id: IDAZAZYB
Source file: D:\Projects\ASB\ASB Country and Thematic reports\Indonesia PhaseII report\Part IV-V .xml
Authors: Thomas P. Tomich, Meine van Noordwijk, Suseno Budidarsono, Andy Gillison, Trikurnianti Kusumanto, Daniel Murdiyarso, Fred Stolle, Ahmad M. Fagi, Iswandi Anas, A.F.S. Budiman, Kenneth Chomitz, Rebecca Elmhirst, Chip Fay, Hubert de Foresta, Dennis Garrity, Danan P. Hadi, Suryo Hardiwinoto, Kurniatun Hairiah, Genevieve Michon, Nu Nu San, Cheryl Palm, Soetjipto Partoharjono, Djuber Pasaribu, Eric Penot, Robert Simanungkalit, Martua Sirait, S.M. Sitompul, F.X. Susilo, David Thomas
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Alternative systems and
technologies must be profitable and socially acceptable for smallholders; if
not they have little prospect for adoption (hence impact). Part IV reports the empirical results of
application in
Assessment Criteria.
Empirical results for
Criteria for smallholders’ socioeconomic concerns:
production incentives, labor constraints, and household food security.
Criteria for policymakers’ objectives: growth and
aspects of equity and stability
This part of the report will
conclude with sections on tradeoffs and complementarities among smallholders’
concerns and policymakers’ objectives and on ‘scaling up’ the assessment from
plots to landscapes and watersheds. Criteria for institutional barriers to adoption, which are concerns to both
smallholders and policymakers, will be considered in Part V.
IV.1Profitability indicators
Since many of the land use
alternatives in Sumatra involve perennials, the appropriate measure of profitability is the net present value (NPV, present
discounted value) of revenues less costs oftradable inputs (fertilizer, fuel,
etc) and of domestic factors of production (land, labor, management) over the
full 25 year period considered in the analysis. Because it can account for input and factor
costs as well as outputs and can handle time by discounting future values, this
measure of total factor productivity is superior to partial measures of
productivity (e.g., yield or output per unit labor).
The policy analysis matrix (PAM) technique
provided the framework for estimating profitability indicators as well as the
indicators of labor requirements and cash flow constraints discussed
below. The ‘PAM’ is a matrix of
information about agricultural and natural resource policies and factor market imperfections
that is created by comparing multi-year land use system budgets calculated at
private and social prices (Monke and Pearson 1989 is the basic reference). Private
prices are the prices that households and firms actually face, so private
profitability – the NPV at private prices -- is a measure of production
incentives. Social profitability, calculated at
economic (shadow) prices, removes the impact of policy distortions and market
imperfections on incentives for adoption and investment. Thus social
profitability —the NPV at social prices -- is an indicator of
potential profitability(or comparative advantage). Divergences,
the difference between private profitability and social profitability, are
indicators of distortions, arising either from policy or from market
imperfections and failures. The
structure of the PAM is described in Table IV.1, which is taken from Monke and
Pearson (1989, p. 19).
As pointed
out by our colleague, Arild Angelsen, the list of potential corrections to
arrive at social prices is quite long.
The adjustments to derive social prices in these analyses focus mainly
on policy distortions arising from trade restrictions. As discussed below, we also used a lower real
discount rate (15% instead of 20%) to capture a rough approximation of the
impact of capital market imperfections on the private cost of capital. We have used the same wage rate in both sets
of calculations, implicitly assuming that there are no imperfections in the
market for unskilled labor. While this
is not completely true, it also seems that these imperfections do not have a
significant effect in the unskilled labor market (see discussion of labor
markets in Section V.4 below). The main
omission here is that prices are not adjusted to reflect costs and benefits of
environmental externalities arising from these production activities, such as
smoke, ecological changes, and loss of watershed functions. These adjustments, which probably would be
significant and which are necessary for the complete analysis, are not possible
at this time because of lack of data.
Filling this gap is a priority for future research, as discussed below
in Section IV.5.
These
studies focus on primary production in agriculture and forestry. To get the complete economic picture,
especially regarding comparative advantage and growth potential, it would be
necessary to extend these analyses ‘downstream’ to include the private and
social profitability of processing activities, especially for timber, rubber,
cassava, and palm oil. Each of these
studies of processing activities (described in Appendix E) would be a major
undertaking in its own right and was not feasible during Phase II work in
Table IV.1 Policy Analysis Matrix
|
|
|
Costs |
|
|
|
|
Revenues |
Tradable inputs |
Domestic factors |
Profits |
|
Private
prices Social
prices Effects
of divergences and efficient policy |
A E I3 |
B F J4 |
C G K5 |
D1 H2 L6 |
1 Private profits, D, equal A minus B minus C.
2 Social profits, H, equal E minus F minus G.
3 Output transfers, I, equal A minus E.
4 Input transfers, J, equal B minus F.
5 Factor transfers, K, equal C minus G.
6 Net transfers, L, equal D minus H; they also equal
I minus J minus K.
Ratio Indicators for
Comparison of Unlike Outputs
Private cost ratio (PCR): C/
(A – B)
Domestic resource cost ratio
(DRC): G/ (E – F)
Nominal protection
coefficient (NPC)
On tradable outputs (NPCO):
A/E
On tradable inputs (NPCI):
B/F
Effective protection
coefficient (EPC): (A – B)/ (E – F)
Profitability coefficient
(PC): (A – B – C)/ (E – F – G) or D/H
Subsidy ratio to producers
(SRP): L/E or (D – H)/E
Source: Taken from Monke and
Pearson 1989, Table II.1, page 19.
To assure comparability
across land use systems (and across ASB sites in Indonesia and Thailand), a
regional short course on application of the PAM approach to natural resource
management and policy analysis was be held in Chiang Mai, Thailand, 1-13 June
1997. Through participation in lectures and computer-based exercises, teams
developed a common methodology for analysis of land use systems. The course,
which was funded by ADB, involved eleven participants from
Table IV.2 ADB-Funded
Grants for Socioeconomic Research in
|
Research Topic |
Researchers |
Institution |
|
Does shifting cultivation
really cause deforestation? Economic analysis of shifting cultivation and
five-year bush fallow in |
Bustanul Arifin
Agus Hudoyo |
Department of Agricultural Economics and Rural
Sociology, |
|
Economic analysis of land
use system for large scale plantations of oil palm and industrial timber
estates |
Retno Maryani
Setiasih Irawanti |
|
|
3. Economic analysis of large scale logging |
Machfudh
Wesman Endom |
|
|
Analysis of the economic
efficiency and comparative advantage of the Sumatran small-holder rubber
using ‘PAM’ method |
Gelar Setya Budhi |
Center for Agro Socio-Economic Research, Agency
for Agricultural Research and Development, Department of Agriculture |
|
Economic analysis of NTFP
extraction in Rantau-pandan, |
Arif Aliadi
Wibowo A. Djatmiko |
The Indonesian Tropical Institute (LATIN) |
Operational definitions for
the six land use types were given at the end of Chapter I.
1. Community-based forest
management,
2. Large-scale commercial
logging
3. Smallholder rubber,
including both rubber agroforests and rubber monoculture.
4. Large-scale plantations of
oil palm and industrial timber estates
5. Upland rice with bush
fallow
6. Transmigration systems,
focusing on cassava and Imperata
cylindrica (alang-alang)
See Tables I.2, I.3, and I.4
for additional specifications of these systems.
Annex E contains the PAMs for the various scenarios and more information
on each of the studies.
All of these studies use the
macroeconomic parameters tabulated below because the data were collected in
July 1997, when the exchange rate was about Rp 2400 / US dollar. By most assessments of economic fundamentals (e.g.,
purchasing power parity), the Indonesian Rupiah was not greatly overvalued at
that time. The consensus was that the
overvaluation of the Rupiah relative to the dollar may have been 10-15% in June
1997. Some expert analysts even expected
the Rupiah to appreciate if it were floated in 1997 (Mc Leod 1997). To almost everyone’s surprise, the collapse
of the Thai Baht in July 1997 spread to the Rupiah (among others). By January 1998, the Rupiah had fallen to over
Rp 17,000 per US dollar. After a recovery below Rp 10,000, it had fallen again
to over Rp 14,000 per dollar in June 1998.
The reasons why Indonesia’s currency fell the furthest and has stayed
down the longest rest with profound problems in its banks and other financial
institutions compounded by the worst social instability and political
uncertainty in 30 years.
The impact on land use
incentives resulting from this monetary, social, and political crisis will be
examined in Part VI. Although the causes
of the regional financial crisis are not yet fully understood, they do not reflect
fundamentals of the productive sectors of
|
Macroeconomic parameters for PAMs |
July 1997 |
|
Exchange
rate |
Rp
2400 / US$ 1 |
|
Wage
rate in |
Rp
4000 / day |
|
Real interest rates (net of
inflation): |
|
|
Private: |
20
% per year |
|
Social: |
15
% per year |
Real interest rates – that is interest rates net of inflation -- are the discount factors
used to value future cash flows in current terms. As in most developing countries, capital
markets in
On the other hand, as
Angelsen has pointed out, ‘desire to claim or secure land rights may modify the
effect of high discount rates.’
An activity with NPV less
than zero is ‘unprofitable’ by definition.
This does not necessarily mean that there are no positive cash
flows. Instead, it means that it would
be more profitable to do other things with the land, labor and capital than to
devote them to this activity. If land is scarce, the NPV estimates
measure returns to land because they are the ‘surplus’ remaining
after accounting for costs of labor (including imputed value of family labor),
capital (through discounting), and purchased inputs.[1] (To the extent that management is a scarce
factor, it also would be included in the residual.) We also present a measure of returns to labor, the wage rate that
sets the NPV equal to zero. This
calculation converts the ‘surplus’ to a wage after accounting for purchased
inputs and discounting for the cost of capital; no surplus is attributed to
land. This measure of returns to labor is
valid when land is abundant and labor is scarce. Returns that exceed the wage, Rp 4000 per
day, mean the activity will be attractive to family members compared to
off-farm work or would justify hiring labor.
Although local land abundance
with household labor scarcity has prevailed historically and certainly
continues in the ASB sites in
For these reasons, and to
facilitate cross-site comparisons, returns
to labor valued at private prices was selected as the indicator of
profitability for smallholders’ production incentives. Private prices are used in this indicator to
reflect actual incentives smallholders faced under policies in effect in
mid-1997.
At the same time, local and
national policymakers increasingly are making public policy decisions under
conditions of land scarcity and labor abundance. Land certainly is a constraint that should be
considered by policymakers in choices regarding development of large-scale
estates versus smallholders and there are other reasons to believe these
development strategies are mutually exclusive (Tomich et al 1995).
Returns to land valued at social prices will be
used as the indicator for potential profitability from policymakers’
perspective. Social prices are used to indicate potential value
added from this alternative if policy distortions and market imperfections were
removed. This impact on value added is
directly linked to policymakers’ growth objectives.
|
Table IV.3 Profitability Matrix, July 1997 |
|
|
|
|
|
|
Land Use System |
RETURNS TO LAND |
|
RETURNS TO LABOR |
||
|
|
|
|
|
|
|
|
|
|
|
|
Wage to set NPV to Zero |
|
|
|
NPV Private Prices |
NPV Social Prices |
Divergences |
Private Prices |
Social Prices |
|
|
Rupiah 000 / ha |
Rupiah 000 / ha |
Rupiah 000 / ha |
Rp / person-day |
Rp / person-day |
|
Community - based forest management |
8.0 to 16 |
9.4 to 18 |
(1.5) to (2.5) |
11,000
to 12,000 |
11,000 |
|
Commercial Logging |
(804) to
(131) |
(32) to
2,102 |
(2,233) to (773) |
(17,349)
to 2,008 |
7,,917 to 31,400 |
|
Rubber agroforest (seedlings) |
1.6 |
73 |
71 |
4,000 |
4,100 |
|
Rubber agroforest (clones) |
(95) to 2,202 |
234 to 3,623 |
(330 to (1,420) |
3,900 to 6,900 |
4,200 to 7,700 |
|
Rubber monoculture |
(167) |
(993) |
(826) |
3,683 |
2,600 |
|
Oil palm monoculture |
275 |
1,480 |
(1,204) |
5,797 |
9,981 |
|
|
(220) to
(76) |
(180)
to 53 |
(37)
to (130) |
2,700 to
3,300 |
3,000 to 4,500 |
|
Monoculture cassava/Imperata cylindrica |
(71) to
360 |
(315) to 389 |
135 to 243 |
3,895
to 4,515 |
4,085 to 4,455 |
Estimates of returns to land
and returns to labor, each evaluated at private and at social prices, are
presented in Table IV.3. The upland rice
/ bush fallow rotation stands out as being unprofitable, either in terms of
potential profitability (returns to land at social prices) or smallholder
production incentives (returns to labor at private prices). For the upland rice / bush fallow system, the
higher (less negative) returns are for the fallow of ten years or more, which
is no longer feasible. The lower (or
more negative) numbers in the range correspond to short fallow shifting
cultivation. These results are
consistent with the disappearance of shifting cultivation in most of
Returns to labor are highest
for community-based forest management (extraction of NTFPs), but these high
returns are dependent on some mechanism to exclude outsiders. Thus, this system plays an important role for
existing communities that can regulate access to forest lands. If, on the other
hand, communities could not regulate access to their forests, one would expect
the returns to labor from extraction of forest products to decline toward the
wage rate. However, even under ‘open
access’ one would still expect returns to labor to exceed the wage rate by some
margin equal to a risk premium. The
risks involved include possibility of failure to find products to extract and
also the risk (and associated costs) of detection by officials, since many of
these activities are prohibited.
The relatively low returns to
land – only slightly above rubber agroforests – suggest that NTFP extraction is
not a feasible alternative for large numbers of people, because there is not
enough land for everyone to practice this extensive livelihood strategy. These results must be interpreted with some
care, however, for three reasons. First,
these extractive activities are highly site-specific. It may be that the study site is not
representative. Only additional studies
can resolve this. Second, as often is
the case, at least part of this community forest is on
The results for commercial logging appear paradoxical,
but this is because of policies that produce the biggest divergences for any of
these land uses. First, the sustainable
logging regulations – if they really are followed – reduce profitability,
mainly by slowing timber extraction.
Second, high export taxes (effectively an export ban) for logs and sawn
timber depressed the domestic prices of logs from 50-70% below comparable world
prices. (Timber export taxes were to be
reduced to 30% by the end of 1998.)
However, timber companies could get around both of these problems. First, as mentioned above, many companies
circumvent regulations on timber extraction. Second, these typically are
vertically-integrated firms producing products like plywood for the export
market. Therefore, the best indicator of profitability of these activities for
logging companies is the figure of just over Rp 2 million per ha, valued at
social prices that reflect world prices of forestry products. When comparable estimates are available for
industrial timber plantations, it seems likely that these will be more
profitable than logging.
By all accounts, illegal
logging is common, which seems inconsistent with these results of negative
returns to logging at private prices.
However, the major cost item for logging concessions -- establishing and
maintaining logging roads -- is not incurred by illegal loggers. If one can get access to timber without
having to invest in infrastructure (and at the same time circumventing various
fees), logging can be very profitable.
One could argue
that the estimated NPV of logging activities of over Rp 2.1 million per ha
(about US$ 875) in mid-1997 should be added to the social profitability for all the other activities and to private
profitability, at least for large-scale estates that often can market timber
felled as a by-product of land clearing.
Recall that natural forest cover is the starting point underlying these
calculations (and all the other estimates in this report). Thus all the forest-derived land uses
(rubber, oil palm, cassava, and even upland rice) started out with felling of
forest timber. And, as already noted,
there is substantial (but as yet unquantified) timber felling in conjunction
with NTFP extraction. Thus, in many
cases it would be appropriate to add the value of the harvested wood to the
profitability of each activity overall.
This modification is debatable for private profitability of smallholder
systems, however, because most of the felled timber is burned instead of
marketed. Yet, this simply may be a
result of trade restrictions that make it artificially difficult for smallholders
to sell timber legally (Section VII.2).
The estimate of timber values was not added to other land uses in the
tables presented in the report, however, because the one-off value of timber
extracted as a by-product of land clearing often exceeds the value of the
derived land use. Thus, although it is technically correct to do so, adding the value of
timber – which admittedly is subject to considerable uncertainty – would simply
obscure differences in profitability among the derived land uses. This problem in presentation is linked to a
problem in conservation: if regulations can be circumvented – as often is the
case -- forest conversion is privately profitable simply for the value of
timber regardless of the subsequent land use.
Of course, for the social profitability calculations, timber values
would have to be balanced against losses of ecological and other environmental
functions of natural forests.
Oil palm is widely viewed as the most profitable
alternative for Sumatra’s peneplains and
The three contrasting rubber systems produce a wide range
of results. First, as already noted, it
is encouraging that returns to labor at private prices are virtually identical
to the market wage for rubber agroforests planted with seedlings. Although these smallholders are the lowest
cost producers of natural rubber in the world (Barlow et al., 1994), returns to land at social prices are not much above
upland rice with a long bush fallow rotation and are well below oil palm
monoculture.
Perhaps the most striking result in Table IV.3 are the
returns to land at social prices for rubber agroforests planted with PB 260
clones, which rival large-scale oil palm monoculture. This system also produces attractive returns
to labor at private prices. These
data must be treated with caution – which is why they are in italics – since
they are based on projections from farmer-managed trials and have not been
verified through broader experience by smallholders. The top of the range of profitability
estimates might actually be attained by 10-25 % of smallholders (
The profitability estimates
for smallholder rubber monoculture planted with GT 1 clonal seedlings provide a
cautionary tale to balance the encouraging projections for rubber agroforests
planted with PB 260 clones. These
monoculture plots were part of a government-sponsored rubber replanting project
that was undertaken with high expectations.
But the disappointing yields that were obtained because of institutional
shortcomings involving supply of planting material, technical information, and
credit – these will be taken up in Part V -- could not offset the high costs of
that project’s approach. Instead of the
high-cost approach in this case of rubber monoculture, the strategy to
introduce clones into smallholders’ agroforests seeks a moderate increase in
yields at minimal incremental costs.
Yet the costly lessons of earlier failures in smallholder rubber
development should be borne in mind (Tomich 1991), including difficulty in
supplying clonal planting material. The
sites studied, for example, were designed to be planted with clones but were
actually planted with clonal seedlings because of this problem.
IV.2 Labor requirements indicators
Table IV.4 presents three
different indicators of labor requirements.
First is total person-days required to establish a system, where
‘establishment’ refers to the period before positive cash flows begin. The two systems with highest potential
profitability in the previous section – smallholder rubber agroforests planted
with clones and large-scale oil palm—both have very high labor requirements for
this phase. However, recall that each
system also had high returns to labor.
Thus, problems in the labor market or credit market that will be
discussed in Part V could impose a serious barrier to adoption, but returns to
labor itself is not a problem here.
More generally, returns to labor valued at private
prices, which was selected above as an indicator of smallholders’
production incentives, also is a good
indicator for smallholders’ concerns with labor constraints if combined with
assessments of institutional barriers in markets for labor and capital.
The two other indicators of
labor requirements in Table IV.4 are closely related, labor requirements for
the operational phase (defined as the period after positive cash flow begins)
and total labor. Both measures are
averaged over time and the units are person-days per hectare per year.
From the perspective of policymakers concerned with
employment generation, total time-averaged labor requirements is a good
indicator that is related to equity and stability criteria. Note,
however, thatwhile labor-intensive alternatives should be attractive for policymakers
who are concerned with job creation, these alternatives will only be attractive
to households if they provide attractive returns to labor, the indicator
discussed above.
For the rubber and oil palm
systems that were evaluated, total time-averaged labor requirements are
similar, ranging between 100 and 150 person-days per ha pa. Harvesting labor is the biggest component in
these systems. Because of lack of
pronounced seasonality in much of
Table IV.4 Labor requirements matrix,
July 1997
(Total labor inputs for establishment
and averages over time for operations and total labor)
|
Land Use System |
Establishment phase (Person-days/ha) |
Operation phase (Person-days/ha/yr) |
Total Labor (Person-days/ha/yr) |
|
Community - based forest management |
na |
0.2 - 0.4 |
0.2 - 0.4 |
|
Commercial Logging |
15 to 100 |
17 to 41 |
31 |
|
Rubber agroforest (seedling) |
271 |
157 |
111 |
|
Rubber agroforest
(clones) |
444 |
74 |
150 |
|
Rubber monoculture |
344 |
166 |
133 |
|
Oil palm monoculture |
532 |
83 |
108 |
|
Upland rice / bush fallow rotation |
na |
15 to 25 |
15 to 25 |
|
Monoculture cassava / Imperata
cylindrica |
na |
98 to 104 |
98 to 104 |
IV.3 Cash flow constraints indicators
Because perennials are so
important among the Sumatran alternatives, our analysis of cash flow
constraints focused on multi-year (rather than seasonal) cash flow constraints
in order to assess whether the investments required by these systems are
barriers to adoption by smallholders.
Table IV.5 takes two perspectives on multi-year cash flow constraints:
years to positive cash flow and the NPV of establishment costs, which we define
as costs prior to positive cash flow.
The imputed value of family labor is included in these establishment
costs because these labor inputs presumably represent foregone earnings in
other activities even if they do not require cash outlay.
By either measure,
community-based forest management is the only profitable system without any
multi-year cash flow constraints. For
the other systems, years to positive cash flow range from 2 years for logging
and cassava to 6-10 years for smallholder rubber and 10 years for large-scale
oil palm. Time is not a constraint by
itself, as evidenced by almost 3 million ha of rubber agroforests that have
been planted by smallholders without any formal credit. The NPV of establishment costs at private
prices, which is derived directly from the PAM cash flows, probably is the best
indicator of cash flow constraints for smallholders. In interpreting these estimates, keep in
mind that the existing rubber agroforests are evidence that the Rp 1.3 million
required to establish them has not been an insurmountable barrier for
smallholders. These estimates suggest
that replacing seedlings with higher-yielding clones in rubber agroforests more
than doubles investment costs to roughly Rp 2.6 –2.9 million per ha. Since
there is no long-term institutional credit for smallholders in
At Rp 8 million per ha,
investment costs for large-scale oil palm plantations are the highest of
all. Investments of this magnitude would
be difficult for many smallholders. But
capital costs for large-scale plantations may be inflated for at least two reasons. First, large-scale oil palm plantations
formerly received heavily subsidized credit from the Government, which would
tend to make them artificially capital intensive. Second, there may have been a tendency among
respondents to overstate investment costs in order to mask the profitability of
these investments. Even more than
rubber, adapting high-yielding oil palm systems as alternatives for
smallholders will require research to develop options that are less capital
intensive.
Table IV.5 Cash flow constraint matrix,
July 1997
|
Land Use System |
Years to positive |
NPV of |
Years to positive |
NPV of |
|
|
Cash flow |
Establishment cost |
Cash flow |
Establishment cost |
|
|
Private prices |
Private prices |
Social Prices |
Social Prices |
|
|
(Years) |
(Rupiah / ha) |
(Years) |
(Rupiah / ha) |
|
Community - based forest management |
na |
na |
na |
na |
|
Commercial Logging |
2 |
820,669 to 869,199 |
2 |
716,917 to 764,238 |
|
Rubber agroforest (seedlings) |
10 |
1,305,536 |
10 |
1,477,735 |
|
Rubber agroforest
(clones) |
6 to 7 |
2,593,458 to 2,862,422 |
6 to 7 |
2,950,338 to
3,303,338 |
|
Rubber monoculture |
10 |
2,085,257 |
10 |
2,192,584 |
|
Oil palm monoculture |
10 |
8,041,847 |
9 |
8,182,015 |
|
|
never |
na |
never |
na |
|
Cassava / Imperata cylindrica |
2 |
na |
2 |
na |
IV.4Household food security indicators
Food nutrient content
measures, as in Table IV.6, can be seriously misleading because food security
derives from the ability to obtain food, including purchases, and not just
capacity to grow it. An unsustainable, low-productivity shifting cultivation system
that is suffering decreasing yields because of nutrient depletion and
increasing variability in yields because of pest problems may be a riskier
basis for securing household food supply than a rubber plot that reliably
produces a steady stream of output that can readily be marketed in exchange for
rice that trades at a stabilized price.
To accommodate land use
alternatives that do not involve foodcrops, our food security indicator is
based on Sen’s (1982) concept of risk of food entitlement failure, which
encompasses trade-based and production-based entitlements to food as well as
security of property rights over productive assets (inheritance and transfer
entitlements). Moreover, one of the key
dimensions of this analysis is the ‘path’ of food entitlement – is it derived
from consumption of one’s own food production, exchange of one’s own production
for food, or working for wages to buy food?
These ‘paths’ determine the measure of risk of entitlement failure. If the path is production of one’s own food, one simple indicator of production risk is
the coefficient of variation of yields.[2] If the path is exchange for food, terms of
trade risk must be considered in addition to production risk. A
simple indicator of terms of trade risk is the coefficient of variation of the
ratio of revenue (price of output times yield) to the price of the staple food,
which for
IV.5 The ‘missing middle’: scaling up from plots to
landscapes
Work is needed to expand the
assessments of sustainability from plot-level agronomic issues to include
environmental externalities at the landscape level and watershed
functions. In addition to the two
existing study areas in Lampung, the ASB-Indonesia Consortium is planning to
have a serious look at the issues of watershed degradation and rehabilitation
in the foothill/ mountain zone of Lampung . This is a zone of major conflicts
between migrants who are attracted by the fertility of the soils (allowing for
coffee production), but who come into conflict with forestry officials who try
to maintain this zone as 'protection forest'. This site, together with Mae
Chaem in Northern Thailand and Manupali in Mindanao, the
The policy-driven agenda will
require new biophysical insights into landscape-level processes
Of soil and water
conservation, as current plot-level insights can not be easily scaled up
(Figure IV.1). The Sumber Jaya area,
halfway between Krui and the North Lampung ASB benchmark area seems eminently
suitable to take up this challenge (see Map 3).
In order to complete the landscape transect, it is necessary to expand
from the present focus on the peneplains and piedmont agroecological zones in
order to include the montane zone and coastal swamps.
Table IV.6
Household Food Security Matrix
|
Land Use System |
Nutritional Value of Food
Produced by the System |
Food Entitlement via: Own Production, Exchange, or Wages |
Risk of Food Entitlement
Failure |
|||||
|
Establishment |
Operation |
Production Risk |
Terms of Trade Risk |
|||||
|
Calories: avg kcal /ha/yr |
Protein: Avg. kg /ha/yr |
Micro-nutrients |
Food |
Non-food |
|
|||
|
Community-based forest
management |
? |
? |
Important |
n.a. |
Own prod’n & exchange |
? |
? |
? |
|
Commercial logging |
Nil |
Nil |
Nil |
Wages |
Wages |
n.a. |
n.a. |
n.a. |
|
Rubber agroforests |
118 |
2.2 |
? |
Own prod’n |
Exchange |
n.a. |
0.13 |
0.26 |
|
Oil palm |
19,800 |
Nil |
Nil |
Wages |
Wages |
n.a. |
n.a. |
n.a. |
|
Upland rice / bush fallow
rotation |
441 - 490 |
8.3 - 9.2 |
Nil ? |
n.a. |
Own prod’n |
0.18 |
n.a. |
n.a. |
|
Monoculture cassava
degrading to Imperata cylindrica |
9,900 |
13.6 |
Nil |
n.a. |
Own prod’n & exchange |
0.06 |
n.a. |
0.22 |

Figure IV.1 Schematic development of the
landscape in a sub-watershed and its effects on storm flow, net sediment loss
and dry-season base flow:
Managing smoke. As will be discussed Part VI, banning burning
has not worked. What policy options and
policy instruments presently exist to manage the recurrent regional problem of too much smoke in the wrong place
at the wrong time? What data would be
useful in designing and implementing a strategy to manage burning in order to
address the smoke problem? What are the consequences of land clearing without
the use of fire? What is the role of remote sensing data? Of studies of
local institutions? What other
types of data or research would be useful to policymakers? If those data were available, how could they
be used? (And, given the inaction to
date, under what circumstances would they be used?)
Changing roles of biodiversity in the landscape. Much
discussion of biodiversity conservation focuses on existence values – i.e.,
preventing extinctions. Landscape
ecology currently emphasizes managing corridors and bufferzones to improve
opportunities for dispersal and recolonization. Much less attention has been given to local
functional values of biodiversity in the landscape (belowground as well as
above), ranging from the tangible (but not yet well quantified) roles of
biodiversity in sustainability and resilience of production systems to less tangible
esthetic and spiritual roles of biodiversity for local people who experience
its pluses (and minuses) daily. Which
among these—and other roles—are felt to be most important at the local and
national level? To what extent is it
feasible to go beyond plot-level measures of richness and to scale-up to the
landscape level? Are there important
functions that are unquantifiable? If
so, how can these be incorporated in the debate? More broadly, how can diverse societies
identify these functional roles of biodiversity and assess tradeoffs with other
public policy objectives?
Loss of watershed functions. National
concern for forest conservation and reforestation often focuses on the loss of
the watershed functions of natural forests. While some land uses may be as good
as natural forest in this regard, land uses differ significantly in their
ability to supply these watershed functions.
Loss of watershed functions can be a combination of:
on-site loss of land
productivity as a result of erosion,
off-site concerns about water
quantity, including annual water yield, peak (storm) flow, dry season base
flow, and groundwater recharge or depletion,
off-site concerns about water quality, including
siltation of reservoirs and environmental damage from runoff of pesticides,
fertilizers, or animal wastes.
Research on this topic will
seek to quantify erosion from natural processes, agriculture or other
activities (such as road construction) and to assess the impacts (positive as
well as negative) of resulting sedimentation and to assess how land use change
affects risks of floods and seasonal water shortages.
IV.6
Tradeoffs and complementarities between smallholders’ concerns and
policymakers’ objectives
Policymakers’ concerns with
potential profitability and smallholders’ concerns with production incentives
and household food security. If they really
are more profitable than smallholder alternatives, all the large-scale systems
involve tradeoffs with smallholder production incentives and household food security,
since such projects often displace local smallholders with little or no
compensation. (In the case of
large-scale logging, there also is a tradeoff with employment creation.)
The potential profitability
of some tree-based alternatives for smallholders (viz., rubber agroforests
planted with clones) appears to be comparable to large-scale estates and
logging. However, this requires further
verification through additional studies of smallholder rubber and other
alternatives, such as smallholder timber and smallholder oil palm. This result holds promise for complementarity
between policymakers’ concerns with potential profitability and smallholders’
production incentives. It also suggests
that policy concerns with equity and mounting concerns about social and
political instability can be addressed through a smallholder-based development
strategy without a significant reduction in economic growth.
If they can be adapted for
smallholders, the treecrop-based systems offer attractive production incentives. Since labor markets appear to work well,
labor should not be a serious constraint to adoption. Thus, smallholder treecrop systems also offer
complementarity with employment creation objectives.
Potential impacts on
household food security depend crucially on government policy regarding rice
marketing. If the government can sustain
its commitment to rice price stabilization, households’ production of treecrops
for sale should not jeopardize their food security. However, it remains to be seen whether rice price policies can be
sustained.
Other potential constraints
to adoption by smallholders will be examined in Part V.
[1] In some
figures, we will use an alternative measure called the internal rate of return (IRR), which is the discount rate that
brings the NPV to zero. The IRR is
technically inferior to NPV for assessment of mutually-exclusive alternatives
(Gittinger 1982), but using it makes the
same point with greater clarity.
[2] The
coefficient of variation is the standard deviation in a series divided by the
mean of the series. It is a relative
measure that expresses variation as a proportion of the average level.