Under the emissions from agriculture, forestry and other land uses (AFOLU), reducing emissions from deforestation and forest degradation (REDD+) is expected to tap the large mitigation potential of conserving and better managing the world’s forests, predominantly in tropical countries. Recent emission data suggest that forest loss contributes less to global anthropogenic greenhouse gas (GHG) emissions than had been estimated in the Intergovernmental Panel on Climate Change (IPCC) 2007 assessment report [1
], but AFOLU emissions from tropical countries, including methane (CH4
) and nitrous oxide (N2
O) predominantly from agricultural land, still represent 31% of total global anthropogenic GHG emissions [3
]. The relative importance of emissions from agriculture has therefore spurred renewed interest in agriculture-based climate change mitigation.
In 2007, FAO’s The State of Food and Agriculture report emphasized the large potential for encouraging farmers to provide ecosystem services, including climate change mitigation, using payments for environmental services (PES) in agriculture as the key instrument. Several analysts have thus called for a whole-landscape perspective to AFOLU-based climate change mitigation as a response to the diverse interrelated factors that contribute to emissions from agricultural and forested land [3
Operationalizing whole landscape management could essentially involve two types of interventions: (1) reducing agricultural expansion, increasing cropland retirement, and forest conservation; versus
(2) changing production technologies and practices. Accordingly, Zilberman et al.
] distinguished between “land-diversion schemes” where land is set aside for conservation, and “working-land schemes” that change production practices and technologies to achieve mitigation objectives. In the following, we employ the related terms “use-restricting
” versus “use-modifying
” to distinguish between the two intervention types.
In tropical countries, current mitigation initiatives rely preferably on use-restricting, often forest- or forestry-based interventions [6
]. Notable exceptions are use-modifying afforestation and reforestation (A/R) schemes strategies. However, even forestry-based mitigation has been ridden with obstacles. A/R initiatives as the only AFOLU measure eligible under the Clean Development Mechanism (CDM) of the Kyoto Protocol, account for only 39 out of 3,379 registered projects approved since the CDM’s inception [7
]. Complicated rules and high transaction costs have been binding constraints, and pilot experiences were often confined to the voluntary market [8
Beyond assessing the biophysical mitigation potential, we thus obviously need to understand potential implementation barriers to alternative AFOLU-based mitigation options in concrete contexts, before we can consider starting points for action. This paper seeks to identify possible low-hanging fruits for climate change mitigation among dominant AFOLU activities and popular alternatives in the Brazilian Amazon region. Based on this scoping assessment, we point to some implications for the design of intervention strategies.
A key criterion for setting priorities among alternative mitigation options is cost-effectiveness. AFOLU-based mitigation cost-effectiveness can be defined as follows:
CE = (BP - L) / (OC + IC) (1)
where CE = cost-effectiveness; BP = biophysical mitigation potential (tCO2); L = leakage (tCO2); OC = opportunity costs ($); and IC = implementation costs ($). All variables on the right-hand side of Equation (1) are subject to measurement and other uncertainties. Ideally, a mitigation option would thus:
(1) Come with high biophysical potential for emission reductions;
(2) Be adoptable at low opportunity costs and low risk of economic failure;
(3) Be carried out at low implementation costs;
(4) And disseminated with low risk of negative spillover effects, e.g., leakage.
Hence, a holistic assessment of mitigation potential goes beyond the biophysical and technological characteristics of different mitigation options; it is also inherently related to intervention design and the local context.
The paper is organized as follows: Section 2
provides a short overview of the Amazon region, and the Brazilian Amazon in particular, and presents the methodologies and data sources used. In
, results are presented according the four intervention criteria sketched above.
concludes with a discussion of implications.
2. Study Area, Methods and Data
The Amazon forest is the largest continuous tropical rainforest on the planet. Between 1989 and 2009, a forest area equivalent to the size of Germany (357 thousand square kilometers) was converted to pastures and agricultural crops in the Brazilian Amazon alone. Here, carbon emissions from deforestation were for 1998–2007 estimated to account for 24% of global carbon emissions from land-use change [9
], but have reduced considerably after 2004 as deforestation dropped sharply [10
]. Enteric methane emissions from its 57 million cattle herd also contribute substantially to agricultural GHG emissions in the region. In countries with large Amazon territories (Bolivia, Brazil, Colombia, Ecuador, and Peru), combined AFOLU emissions account for over 83% of total GHG emissions, thus representing the single most important sector for climate change mitigation in the region [11
Land-cover and land-use change in the Amazon have historically been most dynamic in Brazil, with cattle pasture expansion being by far the most important driver of forest loss [12
]. Apart from cattle ranching, commercial agriculture, small-scale slash-and-burn farming, wildfires, and timber extraction have shown to be significant sources of emission through deforestation, forest degradation, and the use of fire for land preparation [9
Considerable research has been done not only on the prospects of use-restricting conservation schemes in the Amazon, but also on potential use-modifying technological fixes to high GHG emissions, e.g., on intensified cattle production, minimum-tillage cropping, agro-forestry, sustainable forest management, and reduced impact logging. An important part of this research remains confined to the grey literature, which has thus also been consulted for this study. Yet, very few in situ experiments of agricultural innovations exist, and average yield or benefit-cost ratio estimates from controlled field trials seldom allow for realistic comparisons with on-farm established technologies.
As a result of this bias towards controlled field trials, cost-benefit analyses often suggest technological innovations to be both economically (e.g., per-hectare profits) and environmentally (e.g., per-hectare emissions) superior to established practices. In practice, however, adoption rates remain low, such as in the case of agro-forestry systems. Meanwhile, according to the latest Brazilian Agricultural Census in 2006, some technological innovations such as no-till cropping quickly disseminated among commercial farms over the whole region, and now predominate over traditional soil preparation practices. In other words, technological change does happen in the Brazilian Amazon, but currently our analytical means to fully understand and predict it based on economic and environmental indicators are rather limited.
In what follows, we thus identify broad-based tendencies (best bets) with respect to the four mitigation option characteristics outlined above, based on the available literature and secondary data. For each AFOLU mitigation option, we proceed as follows. We first derive indicators of the biophysical mitigation potential of different land-use and technology transitions. Second, transitions with likely emission reduction potentials are then scrutinized for foregone profits or opportunity costs. Third, we establish a simple conceptual framework explaining the cost of implementing these interventions. Finally, we briefly discuss likely spillover effects for selected options.
4. Discussion and Conclusions
We have assessed for the Brazilian Amazon region the bio-physical and economic scope of agriculture (usually, use-modifying) and forestry (predominantly, use-restricting) based mitigation options, in terms of four interrelated performance indicators: bio-physical mitigation potential, opportunity costs and other adoption barriers, implementation costs, and spillover effects. We saw that neither scores equally high on all four accounts; tradeoffs exist between these dimensions, with important implications for the cost-effectiveness and feasibility of currently popular mitigation schemes, such as REDD+. Table 3
summarizes our findings for a selected set of promising and frequently discussed mitigation options and highlights (grey), where high uncertainty about performance indicators suggests future research needs. Mitigation options that exhibit clear adoption trends in the Amazon, such as no-till farming are excluded here as they tend to lack financial additionality.
Avoiding primary forest loss does clearly provide the largest mitigation benefits on a per-hectare basis, provided mitigation initiatives can target forests that are truly threatened. But the lion’s share of projected future deforestation lies in areas with low accessibility. Most of these areas exhibit poor institutional and transport infrastructure, with unclear and conflicting tenure rights featuring among the most prominent barriers to cost-effective mitigation actions [41
]. Incipient REDD projects are thus almost generally forced to invest in establishing basic preconditions for mitigation actions, including leakage control, leading to delays in project implementation and costs [88
]. Assessments purely focused on biophysical mitigation potential and opportunity costs thus probably overestimate the mitigation potential at forest frontiers vis-à-vis opportunities in old frontier areas; except for the limited amount of threatened frontier land under well-established property right regimes, such as extractive reserves or protected areas.
The bio-physical mitigation potential of land retirement, as the other major use-restricting mitigation option, can also be high due to rapid re-growth of secondary vegetation, especially where tree root systems have not been removed by mechanical land preparation. The large areas of low productivity pastures in the Brazilian Amazon as well as extensively used mosaic landscapes resulting from fallow-based farming represent key target areas for land retirement with low opportunity costs. Like primary forest conservation, land retirement potentially displaces other activities, and is thus prone to leakage effects. In the more intervention-friendly environment of old frontiers, land retirement may, nonetheless, represent an area-wise more abundant mitigation option than primary forest conservation.
Summary of performance indicators and related research needs for selected mitigation options (grey color suggests research needs).
Summary of performance indicators and related research needs for selected mitigation options (grey color suggests research needs).
|Mitigation option||Bio-physical mitigation potential per ha (BP)||Opportunity costs (OC)||Implementation cost (IC)||Leakage and spillover effects (L)|
|Primary forest conservation||Very high at most forest frontiers||Many low cost options||Low technological complexity, but high operational costs at new frontiers||High leakage risk|
|Retiring extensive pastures||High||Low cost options, especially where pastures are degraded||Low technological complexity and low operational costs in old frontiers||High leakage risk|
|Sustainable forest management||Medium to high depending on BAU||Medium under currently low prices for certified timber||High technological complexity and high operational costs at new frontiers||Low|
|Reforesting extensive pastures||High||Low or negative depending on species choice and risk profile||Medium to high technological complexity and low operational costs in old frontier areas||Medium|
|Intensifying extensive pastures||Medium||Low to medium depending on state of existing pastures||Low to medium technological complexity and low operational costs in old frontiers areas||Low|
|Integrating trees in crops and pastures||Medium to high depending on tree density||Low or negative depending on tree species and market access||Medium to high technological complexity and low operational costs in old frontier areas||Low|
|Avoiding fire use in annual crop production||Medium to high||Medium depending on crop types and risk profiles||Low to medium technological complexity and low operational costs in old frontiers areas||Low|
Most of the remaining use-modifying mitigation options in Table 3
exhibit lower per-hectare mitigation potential than the two use-restricting options at the top of the table. Apart from “reforesting extensive pastures” all these options are agricultural, but not usually of the type that is associated with a high risk of causing negative spillover effects on other environmental services. Although many of these agricultural mitigation options may exhibit low or even negative opportunity costs in standard cost-benefit analyses, their adoption rate remains low. Adoption research, especially in the agro-forestry literature, suggests several reasons for this apparent paradox [38
]. First, most technological alternatives to business-as-usual land uses perform less well in practice than in experiment station settings. Second, many popular agricultural mitigation options are indeed technologically more complex, and may thus be perceived as inaccessible or riskier from a farmer’s point of view. And third, even in what we termed “old frontiers”, limited market access often prevents farmers, especially smallholders, from capturing prices that justify investments into more climate-smart production systems.
Only the first and second of these three reasons for low adoption rates would appear amendable by project-based mitigation initiatives, whereas the latter requires broader State-led interventions towards infrastructure, public services, and economic development. Past experiences documented in the literature on integrated conservation and development projects (ICDP), as well as recent research on smallholder forestry in the Amazon, suggest that the dissemination of forestry and agricultural innovations is a cost- and time-intensive endeavor with high risks of failure [90
In the context of the Brazilian Amazon, based on our best-bet assessment we thus primarily see scope for two distinct, but not mutually exclusive pathways to land-use based climate change mitigation:
The first, ‘spatially targeted use-restriction’, requires an intervention strategy focused on (a) limiting the expansion of extensive and low opportunity cost land uses, such as conventional cattle ranching, in forest frontier areas; and (b) the retirement of unproductive agricultural and pasture land, some of which now lies in the old frontiers of the Brazilian Amazon.
The second, “technology-specific use modification”, would concentrate on locally facilitating the adoption of technological innovations in both agriculture and forestry. This may involve the technological adaptation of promising mitigation options to local conditions, such as pasture intensification, or the participatory refinement of traditional production systems, e.g., slash-and-burn agriculture, towards a lower carbon footprint.
Our review of performance factors for mitigation options suggests that low-hanging fruits for both strategies exist in the region, but probably only to a limited extent, and often located in separate target regions (Figure 1
and Figure 2
). Our assessment here is nothing but a first regional scoping, which would need to be supplemented by context- and case-specific estimates of service gains and cost of AFOLU-based mitigation initiatives. The increasing number of REDD pilot schemes, of course, also reflects current donor fashions, but suggests equally that forest conservation still has an edge over alternative mitigation options in the Amazon. Managing leakage, non-additionality and non-permanence risks thus represents an important challenge for climate change mitigation in the Amazon.
We identify research needs above all with respect to the opportunity costs and adoption barriers of technological innovations under representative on-farm conditions. In general, very little empirical evidence exists on the costs of implementing mitigation schemes and accompanying policy measures under spatially heterogeneous institutional and accessibility conditions. This includes, among others, economically motivated analyses of land use change that take economic and environmental policies (and their effects on activity displacement, i.e., leakage) explicitly into account.
In any case, however, distinct State-supported interventions in various sectors are required to tap into the potentially large absolute bio-physical potential for climate change mitigation in the Amazon. For example, minimizing leakage from forest conservation and land retirement schemes requires enhancing forest law enforcement on private and unprotected State land, which accounts for the major share of historical and projected future forest loss. In addition, land registration and tenure regulation campaigns are also needed to allow for more effective law enforcement and the establishment of conditional mitigation incentive schemes.
Likewise, agriculture and forestry in the Brazilian Amazon are unlikely to leapfrog onto a technologically more sustainable development path at larger scales without additional public spending for regionally targeted and actor-specific agricultural research and extension. Cases of profitable technological innovations, like no-tillage practices that disseminate without targeted interventions, represent exceptions that may eventually benefit from positive spillover effects once a critical mass of adopters is reached. Promoting general technological development in these sectors comes, nonetheless, also at the risk of causing additional pressure on other environmental services. Well-designed land-use regulations and their effective enforcement thus represent sine qua non conditions for achieving substantial emission reductions in the region. Agriculture and forest-based climate change mitigation in the Amazon poses a challenge not only for developers of project-based carbon schemes. Often much broader development deficits must be addressed to allow for local interventions to cost-effectively promote concrete mitigation options.