Doctoral Dissertation Research: Infrastructure, Mining and Agriculture Expansion versus a
Market-Oriented Biodiversity Economy: Whither the Amazon?
Aghane Antunes - Department of Geography
University of Florida
Project Summary
Amazonia faces a new phase of infrastructure development involving the construction of a multimodal transportation network that integrates port facilities, waterways, bridges, roads, highways,
railways, and tunnels, among others, in order to link resources and commodities to national, regional, and
international markets. In response to this planned major infrastructure buildup, this doctoral dissertation
research improvement project will examine the potential threats that mega-infrastructure projects
associated with massive resource-extraction operations and infrastructure development pose forest
conservation, local communities' livelihoods, and forest-dependent biodiversity-based industry in the
Amazon. We will model these threats in a GIS and remote sensing environment. In this proposed
research, we will use an Amazon basin-wide GIS database documenting current and planned
infrastructure and industrial mining, hydrocarbon extraction, and agricultural activities. The GIS database
will be completed with land cover data, publicly available qualitative and quantitative demographic and
socioeconomic data, in addition to data collected through extensive fieldwork and key informant
interviews. The overarching aim is to identify and demonstrate the impact on land cover changes and
smallholders' decision making caused by mega-infrastructure buildup combined with industrial mining
and agricultural expansion.
Intellectual Merit: The proposed research will investigate the potential impacts of infrastructure build up
on emerging market-oriented strategies to forest conservation, considered one of the few economically
viable alternatives to adapt and mitigate climate change and deforestation in the Brazilian Amazon. The
knowledge generated is important to provide insights regarding how initiatives related to the proposed
biodiversity-based economy will be affected in case an increase in deforestation, population density,
infrastructure materialize. The research will measure, predict and explain critical natural-human
interactions and impacts that should result from the potentially profound transformation in land cover and
demography, driven by strict economic development policies and large infrastructure construction in the
Amazon. This study will be the first study of its kind, exploring the compatibility of large infrastructure
development and market-oriented strategies to conservation. Ideally, the research findings will prove that
infrastructure development has an insignificant influence on efforts to establish a biodiversity-based
economy. This way, the research settles the false dichotomy between conservation and development in
the Amazon region.
Broader Impacts: As a Doctoral Dissertation Research Improvement award, this project will provide
support to enable a promising female doctoral student, born and raised in the Amazon legal region, to
establish an independent research career. This research will also enhance the infrastructure for research and
education through networks and collaboration with Brazilian universities located in the Amazon region
(UFPA and UFMA), facilitating access to unique data resources not generally available to U.S. researchers.
There would also be a strong student mentoring and training component, as the Co-PI will also recruit,
work with and train undergraduate students from underrepresented groups in science (i.e., female, Latino,
low socioeconomic background), who will participate in data collection and analysis.
1) INTRODUCTION AND PROBLEM STATEMENT
The deforestation and degradation of the Amazon rainforest lies at the heart of worldwide concern over
climate mitigation policy (Arima, 2016). Since 2019, deforestation in the Amazon has been on the rise
again, showing a 77% increase over 2018 rates (PRODES, 2019). This comes after decades of successful
control attributed to environmental policies, such as the greening of agricultural supply chains, the soy
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moratorium, and expansion of protected areas and indigenous territories (Nobre et al., 2016; Walker et al.,
2019). Protected areas and indigenous lands are now under assault as the government works to reverse
environmental policies and regulations viewed as impediments to economic development (Walker et al.,
2019). Brazil's current administration aims to expand large-scale mineral and hydrocarbon extraction and
industrial agricultural activities in the Amazon. It also hopes to increase hydropower production
(Bebbington et al. 2018) to provide energy necessary to industry (Bebbington et al., 2018; Simmons et al.,
2018).
These ventures also involve the
construction of a multi-modal
transportation network that integrates
port facilities, waterways, bridges,
roads, highways, railways, and tunnels,
among others, in order to link resources
and commodities to national, regional,
and international markets. Most of these
large-scale investments are part of a
continental plan called Initiative for the
Integration of Regional Infrastructure in
South America (IIRSA). Created in
2000, IIRSA aims to facilitate the
extraction of resources and to improve
transportation, energy, and
telecommunications connections among
South American countries. The goal is
to transform Amazonia into a
continental source of hydropower and a multi-modal transportation hub (Simmons et al., 2018).
In response to this planned major infrastructure buildup, which will have an unknown effect on
environmental services provided by the Amazon basin, this doctoral dissertation research improvement
project will examine the potential threats that mega-infrastructure projects associated with massive
resource-extraction operations and infrastructure development pose forest conservation, local
communities' livelihoods, and forest-dependent biodiversity-based industry in the Amazon. The research
will entail modeling these threats in a GIS and remote sensing environment. We propose to work toward
this goal by using an Amazon basin-wide GIS database documenting current and planned infrastructure
and industrial mining, hydrocarbon extraction, and agricultural activities. The GIS database will be
completed with land cover data, publicly available qualitative and quantitative demographic and
socioeconomic data, in addition to data collected through extensive fieldwork and key informant
interviews. The overarching aim is to identify and demonstrate the impact on land cover changes and
smallholders' decision making caused by mega-infrastructure buildup combined with industrial mining
and agricultural expansion. The research will use a multi-method analytical approach to measure, predict
and explain critical natural-human interactions and impacts that should result from the potentially
profound transformation in land cover and demography, driven by strict economic development policies
and large infrastructure construction in the Amazon.
Problem Statement
Two completely contradictory development pathways are being pursued in the Amazon. One attempts to
maximize forest conservation through the expansion of protected areas and indigenous territories, while
the other seeks to intensify the exploitation of natural resources and infrastructure (Nobre & Nobre,
2019). Some experts, however, have contended that there are alternatives involving extraction of nontimber forest products (NTFP), ecotourism, agroforestry systems (SAFs), and payment for ecosystem
services (PES) (Abramovay, 2018; Bicalho & Hoefle, 2015; Carvalho Ribeiro et al., 2018; Nobre &
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Nobre, 2019). This multifunctional and market-oriented approach to conservation comprises partnerships
between multinational companies and smallholders’ communities producing NTFP commercially through
local cooperatives (Brites & Morsello, 2017; Humphries et al. 2018). Such strategies are not new, and
over the last two decades they have been promoted across the tropics in the Global South (Pokorny &
Pacheco, 2014). However, a new wave is being driven by governments, social organizations, private and
public company coalitions (e.g., The Amazonian Third Way; Amazônia Possível movement). One of the
best known is the so-called Amazonian Third Way initiative. According to its proponents, a biodiversitydriven green economy can potentially provide economic, ecological, and social benefits that outweigh the
economic gains arising from dominant export-oriented and resource-intensive activities practiced in the
region (e.g., mining and mechanized agriculture) (Abramovay, 2018; Nobre & Nobre, 2019). They argue
that protected areas and indigenous territories are under constant siege and may disappear due to
increasing environmental crimes and expansion of commodities frontiers if adequate protective policies
are not enforced (Abramovay, 2018; Nobre & Nobre, 2019). Consequently, the commodification of
common forest goods and ecosystem services is crucial to ensure conservation and social development in
the Amazon (Nobre & Nobre, 2019). Recently, many of these more socially inclusive, less bureaucratic,
voluntary, bilateral partnerships have emerged (Pokorny and Pacheco 2014). In fact, the number of
biodiversity-driven partnerships for trading NTFP to supply the cosmetic, food and pharmaceutical
industries is growing in the Brazilian Amazon (Becker, 2001; Brondízio, 2011; Makishi, 2015; Nobre,
2018). Despite being reasonably promising, the biodiversity-based economy seems to overlap with plans
to expand resource- and energy-intensive industries such as agriculture, livestock, and mining. These still
involve a huge increase in the construction of transport and energy generation infrastructure (e.g.,
hydroelectric, roads, railroads, waterways, and ports). Given these massive investments in infrastructure,
which pose severe threats to forest cover and will almost certainly induce further deforestation, it seems
logical to ask how market-oriented strategies for conservation and associated plans to create a
biodiversity-based economy will be affected by resource-extraction and infrastructure expansion. In the
face of this scenario, a central question remains: to what extent does this biodiversity-based economy
provide a viable approach to long-term forest conservation and social development in the Brazilian
Amazon? To answer this broad question, a subset of guiding questions will be used to empirically and
theoretically determine the implications of the intensification of extractive activities and infrastructure
construction for economic development and conservation in the Brazilian Amazon: (1) What patterns
and trends do initiatives for developing a biodiversity-based economy exhibit across the Amazon
basin, and how does it overlap with the plans to expand infrastructure and industrial mining and
agriculture? (2) What is the prospect for small farmers, given the expansion of mega-infrastructure
projects? (3) Are extractive industries expansion and biodiversity-based markets incompatible with
each other, or can they coexist?
The interplay between these two major development models being pursued in the Amazon has been
overlooked. The lack of information available on these matters presents a problem for planning agencies,
NGOs, government officials, and research institutions that seek to better understand the compatibility
between a biodiversity economy and infrastructure development, enabling the expansion of large-scale
agricultural and extractive industries in the Amazon. We argue that the two are incompatible -- that there
will be spatial overlap between these two development models that will create spaces for conflict and
increased deforestation.
This proposal is timely because the magnitude of these planned infrastructure projects in the Amazon
region is unprecedented (Simmons et al., 2018; Walker et al., 2019). Specifically, they encompass a
logistical system of waterways, port facilities, railways, expansion, and modernization of roads, in
addition to pipelines and electrical power systems. If the full IIRSA portfolio is implemented, together
with other independent projects being planned in the region, it will open the Amazon region to a new
array of global drivers of change that will stimulate deforestation, posing a wide range of environmental
risks (Simmons et al., 2018). Some scholars have warned that deforestation in the Amazon should not
exceed 40% of forest area, to avoid potentially irreversible “tipping points.” (Lovejoy & Nobre, 2018;
Nobre & Borma, 2009). The crossing of this threshold may trigger severe, irreversible negative impacts
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on rainfall recycling, leading to a biome-shift throughout most of the central, southern, and eastern
portions of the Amazon from tropical rainforest to degraded savanna. That is to say, once past this
threshold, forest dieback (or “savanization”) might gradually take place (Lenton et al., 2008; Lovejoy &
Nobre, 2018; Nobre & Borma, 2009). The savanization threatens environmental security through
potential impacts on the carbon cycle and loss of biological diversity, which will likely have serious local
and global environmental and economic consequences (Lovejoy & Nobre, 2018; Marengo et al., 2018;
Nobre et al., 2016; Walker et al., 2019). Human drivers have already cleared an estimated 17% of the
Amazon forests (Lenton et al., 2008). Consequently, we are on the verge of crossing the Amazon tipping
point place (Lovejoy & Nobre, 2018). (Lovejoy and Nobre 2018). There are good reasons to expect that
the physical infrastructure build-up planned for the Amazon, which also makes viable the expansion of
the cattle industry, will result in massive deforestation in excess of the predicted 40% tipping point
(Lovejoy & Nobre, 2018; Oyama & Nobre, 2003). Efforts to curb Amazonian deforestation are thus more
urgent now than ever.
2) PROJECT GOAL AND OBJECTIVES
Our proposed research seeks to evaluate the impacts of infrastructure-induced development on
conservation efforts, including protected areas (PAs) and market-oriented biodiversity-based activities
that occur in or near PAs. We propose to achieve this goal with hypothesis-testing based on GIS,
socioeconomic, and remote-gathered data capable of projecting how the infrastructure investment and
expansion of extractive activities will affect PAs and activities related to the biodiversity-based economy.
In our effort to determine the effects of infrastructure build-up, we will pursue two main goals. (1)
Implement spatial econometric models simulating the effects of infrastructure upon the economy
and deforestation; (2) Simulate different scenarios for infrastructure investment, specifically the
IIRSA plan.
We will assemble data and implement spatial and Bayesian econometric models to predict environmental
and socio-economic impacts caused by a given infrastructure project. The goal is to be able to point out
the best infrastructure projects, taking into consideration all Amazonian residents, including indigenous
and local communities, as well as societal interests in South America. These interests include also
maximizing the return for global investors and fulfilling local residents' legitimate aspiration to economic
growth and shared prosperity. In short, we seek to indicate through simulation which projects of the full
IIRSA portfolio can be truly beneficial to forest conservation and social and economic development,
especially with a view to sustain local communities' welfare and minimize the adverse effects of
development on their livelihoods. The more sustainable projects will be identified through simulations
carried out through econometric projection models.
Outcomes of these models will allow decision-makers to assess and compare multiple possible
development scenarios concerning the impact of a specific infrastructure project on a given location.
Cartography maps depicting the different scenarios and options for infrastructure combinations will be
produced so that stakeholders can assess and compare the impact associated with each set of
infrastructure. These projections should provide a picture of the future that can be used to inform
infrastructure investments in the Amazon. With this, we seek to identify infrastructure projects whose
implementation does not result in complete environmental destruction, undermining the pivotal ecological
role the rainforest plays locally as well as globally. The findings will have implications for policy
planning, decision making, and sustainability in the Amazon region.
3) PROJECT HYPOTHESES
We argue that infrastructure and industrial extractive activities expansion may reduce transportation costs
and increase accessibility, enabling other market opportunities to arise in forest frontier areas, increasing
household economic choices. That is, land use decision-makers (small farmers) may have more
opportunities to maximize economic yield. Rationally, they may choose a more profitable activity than
NTFP extraction, whose revenue is often marginal. We further argue that population growth caused by inmigration and land speculation may also come into play with more accessibility, leading to increased
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deforestation and land degradation. Finally, we argue also that the gain of accessibility caused by
investments in infrastructure might change the viability of the purposely green economy as a strategy to
promote forest conservation and social welfare. We theoretically and empirically address these potential
impacts with a set of four hypotheses:
H1: We hypothesize that infrastructure and industrial mining and agriculture expansion overlap spatially
with the long-hoped-for biodiversity-based economy.
H2: We hypothesize that industrial agricultural expansion, as a proximate driver of forest cover loss, will
lead to increases in cattle production and pasture lands at the community level.
H3: We hypothesize that new infrastructure will trigger underlying socioeconomic drivers of forest cover
change, such as population density and higher in-migration rates (based on a theory of cumulative
causation and industrial agglomeration), leading to greater deforestation.
Background: Tropical forests are the most biologically diverse ecosystems on earth, housing more than
half the world’s biodiversity (Myers et al. 2000; Soares-Filho et al., 2006). Their destruction through
deforestation and environmental degradation is a prime global concern. Forest loss triggers destructive
ecological consequences at local, regional, and global levels (Arima, 2016; Pfaff & Walker, 2010),
including impacts on biodiversity, climate hydrology, and global carbon cycle and sustainable
development (Humphries et al., 2018). Brazil is one of the most economically affluent and
environmentally diverse countries on earth, with an estimated 463 million hectares of natural and planted
forests that cover approximately 55% of its territory (Brazilian Forest Service, 2013; SFB, 2019). These
make up the world’s largest contiguous intact tropical forest (Arima, 2016; Myers, 1988; Pereira,
Simmons, & Walker, 2016; Soares-Filho et al., 2004) and account for roughly 30% of all the world's
remaining tropical forest (IPCC 2013). In recent discussions about the future of the changing Amazon, a
point of contention has been whether the Amazon should be set aside, spared of any further development.
Many scholars believe the Amazon rainforest deserves more extensive protection, since little is known
about its existing biodiversity (Silva et al. 2005; Lewinsohn & Prado, 2005; Peres, 2005). The Amazon
Rainforest today comprises an area of approximately 5.4 million km2, about 87% of its original extent.
Brazil alone accounts for 62% of the entire Amazon biome (Malhi et al., 2008; Myers, 1988; Soares-Filho
et al., 2006). Consequently, Brazilian policies to promote development and conservation are crucial for
the future survival of the Amazon biome.
The stability of forest-climate balance in the Amazon is disturbed by anthropogenic drivers of change.
Tropical deforestation is one of the most critical of those drivers (IPCC, 2013). Several studies have
indicated that continued land clearing will result in drastic consequences, including the conversion of
more than 50% of the Amazon into a degraded savannah (Lenton et al., 2008; Lovejoy & Nobre, 2018).
This change will compromise the forest’s ability to provide critical ecosystems services (e.g., climate
regulation, carbon sequestration, and fire control) (Nobre & Borma, 2009). Deforestation can also
accelerate global warming and its side effects, including severe flooding, changes in rainfall patterns,
river regimes and soil productivity (Laurance et al., 2015; Salazar, Nobre, & Oyama, 2007). Those most
harmed by all these changes will be the poor small farmers who have few alternatives available to meet
subsistence needs, whose livelihoods depend on the existing biodiversity (Brondizio & Moran, 2008;
Nepstad et al. 2008; Salazar et al., 2007). As the world’s largest intact tropical forest, the Amazon
occupies the central position in the global conservation agenda devoted to counteracting climate change
given the potential threat deforestation represents to global environment security (Simmons et al. 2007;
Soares-Filho et al., 2006). Due to its inherent large-scale global climate drivers (i.e., teleconnections),
Amazonian deforestation is one of the most critical environmental problems of our present era ((R.
Walker et al., 2009). Efforts to curb Amazonian deforestation are now more urgent than ever.
Given these threats and related growing concerns, the Brazilian Amazon has garnered much attention
surrounding issues of climate change, deforestation, greenhouse gas emissions, and recent global climate
change agreements to counteract tropical deforestation (Walker et al., 2019). Deforestation in the
Amazon, triggered by development, has raised concerns over the cumulative effects of large-scale
infrastructure projects on global warming and climate change, and ultimately on global security
(Simmons et al., 2018; Walker et al., 2019). Previous researchers have noted that large-scale
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infrastructure and industry operations implemented on the grounds of generating regional development,
have generated revenue for Brazil along with some national and international investors. However, this
wealth did not translate into improvements in the areas affected by these projects as the social indicators
in the region remain the lowest in Brazil (Palheta Da Silva 2007; Godfrey and Thypin-Bermeo 2012;
Simmons 2016).
The sustainable alternative agenda proposed for the Amazon, in turn, consists of a multi-functional
combination of assumed compatible activities, such as NTFP extraction and trade, agroforestry,
community forest management, biodiversity certified fair-trade agreements, ecotourism, and payments for
environmental services, aiming at conserving the forest while also creating cash income opportunities for
small farmers. One of the overarching goals of this alternative strategy is to make the Amazon rainforest
more valuable if left standing than its potential value in timber and other more destructive activities
(Bicalho and Hoefle 2015). The contribution NTFP make to rural livelihoods, and the fact that their use is
less ecologically destructive than other land-uses (mineral extraction, logging, large-scale agriculture, and
pasture, etc.) have supported the belief that the intensification of NTFP production could be conducive to
both conservation and development goals (Arnold & Ruiz Pérez, 2001; Duchelle, 2009; Ros-Tonen et al.,
2008; Wollenberg & Ingles, 1998). The proposal gained strength in development policies in the Amazon,
supported mainly by international donors (Homma, 2018), and has motivated different proposals to
develop market-oriented NTFP production within the region (Arnold & Ruiz Pérez, 2001; Guedes et al.,
2012; World Bank, 2009). Proponents assert that the sustainable production of NTFP is a viable way to
mitigate and adapt to climate change by reducing tropical forest deforestation, while at the same time
providing income opportunities for rural poor communities (Brites & Morsello, 2016; Morsello et al.
2012; Rizek & Morsello, 2012). According to this perspective, an array of forest products, including palm
oils, medicinal plants, and others, can be produced sustainably for growing markets (Morsello, 2006;
Perz, 2004).
The commercialization of NTFP, however, has also generated a good deal of criticism from other
researchers, who present a less optimistic view concerning the alleged conservation and development
link. Several scholars highlight that the production of NTFP is insufficient to promote conservation,
alleviate poverty and increase the income of small farmers (Browder, 1992; Dove, 1993; Godoy & Bawa,
1993; Homma, 1992). Homma (1992), through a theoretical model, demonstrates that an increasing
demand for NTFP tends to push extraction beyond sustainable thresholds, leading to a typical boom-andbust cycle and degradation. Many products that were very important in the economic, social and political
development of the Amazon in the past, such as “backlands drugs” and cocoa (Theobroma cacao L.) in
the colonial period, rubber (Hevea brasiliensis M. Arg.), Brazil nut (Bertholletia excelsa), palm heart, and
acai (Euterpe oleracea Mart.), as well as wood, are not relevant any longer to the regional economy. The
sustainability of these extractive resources systematically changes as an effect of technological progress,
the development of economic alternatives, population growth, stock reduction, wage levels, and prices,
among other factors (Homma, 2012). Therefore, the extraction of NTFP as a viable solution for the
economic development and conservation of the Amazon should be considered with caution (Homma
2012). It has also been stressed that NTFP management may lead to the simplification of ecosystems by
increasing the frequency of species of commercial interest, greater dependence on external actors, greater
vulnerability to market demand and price fluctuations, no substantial poverty reduction, rise of social
inequalities, changes in traditional and cultural values, and community conflicts (Rizek; Morsello, 2008;
Homma 2018; Hans-Jurgen & Dietz 2014). The argument in favor of market-oriented NTFP extraction is
that while traditional commodities such as soybean, timber and minerals require infrastructure for
transport and multiple break-of-bulk logistical points, usually leading to land-use change, massive
environmental impacts and in-migration, innovative biodiversity products are lighter, easier, and cheaper
to transport. They consist, for example, of small jars containing essential oils transformed in higher
economic value-added products for the cosmetics, vaccines, and pharmaceutical industries. They do not
necessarily lead to in-migration and new human settlements in the rainforest, or to other economic
activities that normally involve forest-clearing and fragmentation. Proponents want to promote a shift in
the emphasis on what is economically produced in the region from prevailing intensive resources
6
extraction and infrastructure to a novel biodiversity-based economy focused on innovation. In theory, this
shift would lead to a structural land-use change reducing dominant economic activities that historically
have been responsible for massive deforestation and other negative externalities (Nobre et al. 2016; Nobre
and Nobre 2019). The proposed study affords a timely opportunity to empirically explore how business
incentives and NTFP production affects small farmers' income and land-use decisions, which configures a
broader socio-ecological impact, given the prominent role the engagement in NTFP markets fulfills in
social welfare improvements and in the integrated efforts to reduce deforestation. Another major
contribution of this research will be to illuminate the influence of new infrastructure mega-projects on
accessibility, new markets and opportunity costs, technology availability, and technical ability -- factors
that are critical for both conservation and biodiversity-focused markets.
Theoretical Framework: This proposal uses a poststructuralist Political Ecology (PE) framework, which
integrates concerns and insights of ecology and political economy (Blaikie and Brookfield, 1987;
Rocheleau, 2008). In geography, PE lenses address environmental issues beyond land change, providing a
critical context to economic issues that have a spatial pattern. It is also concerned with sustainability,
social, economic and political vulnerability, and persistent poverty (Simmons 2004; Turner and Robbins
2008). A more recent wave of PE focuses on Coupled Human-Natural (CNH) systems addressing the
connections between these two subsystems (human and environmental), hence making possible a more
comprehensive analysis. Issues of rural communities’ adaptation to climate change; global commodity
chains and other drivers of globalization -- and their hierarchical forces interacting across spatial scales -are examples of problems tackled by political ecologists (Simmons 2004; Turner and Robbins 2008).
Contemporary political ecologists assert that deforestation cannot be solved solely by policies creating
protected reserves, and that understanding the very causes pushing deforestation and environmental
degradation is key. They emphasize that it is common to attribute to small farmers the blame for
deforestation and forest degradation, contending that the reasons poor small farmers have been pushed to
forest frontiers -- bringing deforestation -- is what needs to be addressed. According to this theoretical
framework, a peasant farmer is a family farmer who depends on natural resources and maintains limited
relations to outside markets (Caldas et al. 2007). Specifically, the family farmer makes up a social
category comprising the rural poor (landed and landless), who typically derive their traditional livelihood
from small-scale agriculture, extractive activities, and sometimes off-farm labor (Pereira, Simmons, and
Walker 2016). Hence, peasant households may be market-oriented or not. More likely, they may be some
combination of both (Pereira, Simmons, and Walker 2016). Because of their predominant cultural and
socioeconomic characteristics, scholars agree that small peasant farmers do not perfectly fit into the
conventional binary classifications of social development, which consider families to be either autarkic or
integrated into the capitalist market (Brondizio et al. 2009). In fact, rural smallholders in the Amazon are
no longer autarkic peasants living in unexploited remote areas. They are now entirely engaged in the
global economy (Pereira, Simmons, and Walker 2016). But distant parts of the world experience the
effects of the global economy differently. How the dynamics of the capitalist world-economy unfold in
these remote and rural communities must then be examined. Most of the work addressing peasant
households is context-oriented, survey-based, committed to interpreting interconnections between land
uses, land cover and household economics, as well as traditional market factors, such as transportation
costs. Demographic characteristics, such as family size, length of family residence on the property, and
accessibility to external markets, are also remarkable explanatory variables in studies adopting this frame
in Amazonian research sites (Brondizio and Moran 2008; Perz and Walker 2002; Walker et al. 2002). A
geography-centered PE theoretical framework, then, furnishes an interdisciplinary analytical
interpretative structure that will allow this study to determine the impacts of infrastructure-induced
development on Amazonia’s Coupled Natural Human (CNH) systems, addressing how such impacts may
affect the development of biodiversity-oriented markets and influence local-to-regional land-use
decisions, ecological degradation, and ecosystem services.
Therefore, in this proposal, we will apply a Political Ecology frame integrated with Land Change Science
(LCS) and the so-called New Economic Geography (NEG). The integration of these interdisciplinary
scholarship tends to be the most productive. In fact, the integration of LCS and PE is seen as key
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approaches to understanding today’s most pressing environmental problems (Brannstrom & Vadjunec,
2013). Economic Geography, as a subdiscipline of Human Geography, is concerned with defining and
explaining different places and spaces where economic activities occur (Gregory, Johnston, Pratt, Watts,
& Whatmore, 2011). Its prime interest is the spatial distribution of production and the use, and
transportation of natural resources, goods, and services, and their implications on the natural and human
environments, as well the dynamics of the global and regional economies (Stutz & Warf, 2012). Recent
developments in geographic scholarship arose with the emergence of New Economic Geography (NEG),
seeking to investigate the spatial organization of economic activities and the increased range of economic
agglomeration in geographic locations or spaces. It incorporates quantitative methods of measurement,
especially spatial econometrics modeling techniques, to deal with peculiarities induced by space in
regional science and land-use and land-change models (Luc Anselin, 1988). Recently, there has been a
flourishing interest in new analytical and modeling methods, even though there is no comprehensive, upto-date literature discussing the collection of methodological approaches available straightforwardly (Luc
Anselin, 1999; James P. LeSage, 2008). Current methods applied by economic geographers include
Geographic Information Systems (GIS), mathematical models, qualitative assessments based on
interviews and field work(Stutz & Warf, 2012), and remote sensing.
4) RESEARCH DESIGN AND METHODOLGY
To answer the questions and hypotheses that motivate the research, this proposed project takes a twoprong approach, one of which addresses the social aspects of the research questions, and the other,
associated with econometric modeling and regional sciences theory. As for the social questions, these will
be addressed based on a survey administered to the smallholders and key informant interviews. The
questionnaire will elicit information about household demographics and farming systems.
Spatial Econometric and Regional Sciences Theory: Economic geography and regional science studies
rely heavily on econometric statistical procedures and spatial data linked to points in space. Applied
econometric regression models depend on cross-sectional spatial data collected about points in space,
such as households, towns, regions or states. Many economic processes and agricultural data, including
site-specific crop yield data, land managers decisions, technology adoption, welfare participation, price
and housing decisions, and trade flows, among others, are expected to be spatially structured
(autocorrelated and heteroskedastic), which violates the assumptions of classical statistics regarding
independence of observations and homoscedastic error terms. (Anselin, 1988, 1999; LeSage, 2014). Two
major complications arise when data carries a locational factor: (1) spatial dependence, and (2) spatial
heterogeneity (LeSage, 2014). Although conventional regression models such as ordinary least squares
(OLS) models would be the common statistical estimation method for the analysis we propose in this
research, the “cross-sectional” nature of the data present the potential problem of spatial dependence.
Spatial dependence occurs when values at one place depend on values of neighboring observations at
close places, which violate the assumption of independence between observations. In the presence of
spatial correlation, OLS estimates will likely be inconsistent (L Anselin & Bera, 1998; LeSage, 2009).
Spatial heterogeneity arises when the relationship between observations differs across the spatial data,
which infringe the assumption that a single linear relationship occurs across the sample observations
(LeSage, 1999; LeSage, 2014b). The occurrence of these two spatial effects problems (i.e., spatial
dependence and spatial heterogeneity) violate classical regression model assumptions. In general,
traditional econometrics methods have ignored these two issues that violate the Gauss-Markov
assumptions, adopted in conventional regression modeling. These assumptions specify that when a linear
regression fulfills the Gauss-Markov premises, an OLS regression generates the best possible unbiased
coefficient estimates for any linear estimation procedure. Failure to consider this may lead to incorrect
estimates (LeSage, 2009). It is almost impossible to avoid spatial problems and heteroskedasticity in the
error terms using spatial data, be they big or small, from forested or deforested areas, rural or urban
regions, economically developed or not. In such a case, coefficients may not be as significant as they
might look (Andersen & Reis, 1997). These issues give rise to the need for alternative, more robust
estimation methods to avoid biased or inaccurate inferences (Anselin, 1988; LeSage, 2009; LeSage,
1999). Several spatial multivariate regression models have been developed to handle spatial problems
8
(e.g., maximum likelihood, spatial Durbin model, robust Bayesian variant models). Determining the most
appropriate method from the plethora of possible alternative modeling procedures seems a daunting task.
Examples of such spatial models are Spatial Autoregressive-Regressive (SAR), Spatial Autoregressive
Error (SEM), and Spatial Durbin (SDM) models that were popularized by Anselin’s pioneering work
(1988). Most of the literature on statistical testing of alternative model specifications has built on this
family of nested models (LeSage, 2014b). This estimation modeling approach has become a cornerstone
in economic geography and econometric studies since such models not only can deal with spatial effects
problems appropriately, but also can handle spatial spillovers and omitted explanatory variables -- aspects
also present in spatial-dependent data (LeSage & Pace, 2009). Overcoming problems of simultaneous
spatial dependence and heterogeneity, which typically arises in cross-sectional spatial data, motivates the
use of spatial econometric techniques in this research. Thus, in this proposal, we will specify and test a
variety of specialized statistical methods of spatial regression (spatial and Bayesian models) to avoid
biased or inaccurate inferences.
Modelling approach: The model specifications will be heavily based on MATLAB functions available on
LeSage’s spatial econometrics toolbox available at http://www.spatial-econometrics.com. The models to
be estimated in this proposed research will be informed by Arima (2016), which is considered "state-ofthe-art" in its applied modelling approach, as well as Walker (2004), which is still a reasonable summary
of the development of the type of explicit spatially models with a focus on the deforestation in the
Amazon. These models are theory-based, therefore, they completely differ from other families of spatial
models, such as agent-based, neural net, and CA Markov, among others.
We will specify a Bayesian Economic Model (BEM). This is a state-space model with coefficients
reflecting the impact of infrastructure buildup. Applications of such model are, to our knowledge, nonexistent. We chose Bayesian estimation approach because it can accommodate inherent uncertainty in
both sample data (observation error) and in the representation of the economic system (process error).
Bayesian models produce meaningful posterior parameter distributions under such conditions, which can
otherwise impose severe limitations on estimation using other methods. Bayesian models can also utilize
data collected in disparate years, necessary given varied data sources.
Data: Models will be estimated using county data from a variety of sources, in particular an existing
infrastructure database that the co-PI have already organized (Table1), in addition to socio-ecological
database collected by the Amazon Dams Network (Tucker Lima et al. 2016) and fieldwork data. Initial
spatial data on protected areas, indigenous territories, land ownership and use, forest management,
climate, population, vegetation and soil type and characteristics, population, and productive activities will
be obtained for five regions in the Amazon basin with significant NTFP production and management
activities (define areas based on location of the main productive chains).
Table 1. Existing data on infrastructure projects plans.
Database
IIRSA/Cosiplan
Infrastructure
Projects (Railroad;
Train station;
Railroad;
Highway/Road;
Port; Lake; River;
Administrative
Area; Border
Crossing)
Layers PNL
(Programa
Nacional de
Spatio-temporal
resolution
Format
Acquisition date
2015
GIS layer (.shp)
2019
2017
GIS layer (.shp)
2019
Source
IIRSA/Cosiplan
Planning and
Logistics Company
9
Logistica)
(Highways,
railroads,
waterways and
pipelines)
- National Logistics
Plan (NLP)
Hydroelectric dams
2019
GIS layer (.shp)
2019
Ports and
Waterways
2018
GIS layer (.shp)
2019
Indigenous Lands
2019
GIS layer (.shp)
2019
Roads Network
(State and Federal)
2015
GIS layer (.shp)
2019
National Agency for
Electrical Energy
(ANEEL) - Sistema
de Informações
Georreferenciadas
do Setor Elétrico
(SIGEL)
National Waterway
Transportation
Agency (ANTAQ) Plano Nacional de
Integração
Hidroviária (PNIH)
National Indian
Foundation
(FUNAI)
National
Department of
Highways (DNIT)
These shapefiles will be converted to variables that will be used in the model specification. For example,
accessibility of a county will be proxied by a) distance to urban center/city, b) extension of the new road
and waterway network; c) length of main rivers in region; and d) the level of forest clearing in
neighboring municipalities. With more accessibility, population densities increase especially in early
settled areas. Land becomes scarcer and land prices increase. To capture the effect of land availability in
our empirical model, we use the following four variables gathered from census and other public available
data: a) rural population density; b) land prices; c) share of cleared land. Project implementation: The
phases of the project are the fieldwork interviews and the GIS and statistical analysis. The funds
requested are for conducting the fieldwork. In the sites, socioeconomic data will be collected in addition
to participant observation, interviews, and oral histories of involved communities and key informants,
which will be coupled with archival research to form interpretive explanations. We seek a stratified
sample of 75 interviews with small farmers in each of the four sites and a total of 30 experts and key
informants based on varies locations. Due to difficult and distant access to farm lots, the co-PI expects to
take five interviews per day in rural areas with the assistance of local graduate students, totaling of 225
sample interviews, at least.
5) EXPECTED PROJECT SIGNIFICANCE
Intellectual Merit: The proposed research will predict the potential impacts of infrastructure build up and
expansion of industrial extractive activities on market-oriented strategies to forest conservation,
considered one of the few economically viable alternatives to adapt and mitigate climate change and
deforestation in the Amazon. The knowledge generated, which integrates land-change science (LCS) and
political ecology (PE), is important to provide insights regarding how initiatives related to the proposed
biodiversity-based economy will be affected in case an increase in deforestation, population density,
infrastructure of transport and energy materialize. The research will measure and explain critical
interactions and impacts that should result from the profound transformation in land cover and
10
demography driven by large infrastructure construction and strict economic development policies. This
knowledge makes significant contributions to the advancement of interdisciplinary human-environment
work, especially in CNH systems science, since it will enhance our ability to analyze and feedbacks in
dynamic human-environment interactions.
Broader Impacts: The proposed research will investigate the potential impacts of infrastructure buildup on
emerging market-oriented strategies for forest conservation. Such strategies are considered one of the few
economically viable alternatives to adapt and mitigate climate change and deforestation in the Amazon.
The knowledge generated will provide insights regarding how the proposed bio-nature economy will be
affected in the case of an increase in deforestation and population density, transport and energy
infrastructure. As a Doctoral Dissertation Research Improvement award, this project will provide support
to enable a promising female doctoral student, born and raised in the Amazon legal region, to establish an
independent research career. The co-PI's personal, academic and relevant professional experience and
extensive network in Brazil and in the Amazon region makes her ideally suited to carry out the proposed
research. This research will also enhance the infrastructure for research and education through networks
and collaboration with Brazilian universities located in the Amazon region (UFPA and UFMA),
facilitating access to unique data resources not generally available to U.S. researchers. There would also
be a strong student mentoring and training component, as the Co-PI will also recruit, work with and train
undergraduate students from underrepresented groups in science (i.e., female, latino, low socioeconomic
background), who will participate in data collection and analysis. In addition, this research will enhance
interactions and collaborations with governmental planning agencies, governmental affairs firms, and
think tanks that control the legislative agenda and shape public policies in Brazil and in the Amazon. The
PI and Co-PI’s extensive work in the region will enhance considerably this potential. The Co-PI,
specifically, is from Sao Luis, capital of the state of Maranhão within the Amazon legal area. She worked
for several years in private multinational companies with operations in the Brazilian Amazon, including
large-scale hydropower construction and mining, port and railway projects. These professional
experiences motivated her master's thesis, which addressed corporate-community partnerships between
the cosmetic industry and small peasant farmers engaged in the non-timber forest products (NFTP)
extraction in the Amazon. In this research, she used household-level data in a spatial econometric
modeling approach assessing whether the engagement in the commercialization of NTFP and membership
in company-community partnerships bring about statistically significant changes in the overall household
income level. To estimate this relationship, she implemented a host of conventional spatial and spatially
explicit regression models, including conventional OLS with spatial variables, spatial autoregressive
(SAR) model, spatial autoregressive error (SEM) model, spatial durbin (SDM model, in addition to
alternative spatial Bayesian models. An article derived from this thesis research was accepted to be
published in the interdisciplinary peer-review journal Land (in review). Overall, findings show that the
commercialization of NTFP does not have any effect on the total income of the households studied.
However, membership in cooperatives tied to company-community agreements is positive and
significant, and results in increases in total income at the household level. The proposed Ph.D. research
will build off this earlier master’s research, extending to examine the potential threats from large-scale
infrastructure projects planned for the Amazon basin. The preliminary master’s thesis, in which a suite of
econometric spatial and conventional regression models was applied, confirms the feasibility of the
research and methods, as well as the ability of the co-PI to conduct the proposed research. Results,
including in the form of maps and geo-databases showing and quantifying where infrastructure
development should occur, and potential land-use changes as well as provision of ecosystem services, will
be disseminated broadly to the scientific community in standard academic outlets, as well as in meetings
with the local communities and research groups, including the Amazonian Conservation Team, a
collaboration of peers that emerged from the Tools and Strategies Workshop held at the University of
Florida in 2017, in which the PI is the leader. Findings will be made available also to relevant policy- and
decision-makers to increase understanding and applicability of the research findings. This outreach will
comprise not only the publication of articles in English and Portuguese in relevant, high-impact journals,
11
but also the production of specialized communication material (e.g., releases, white-papers, pitches,
Youtube videos) to be sent to environmental journalists covering environment-related issues, and news
media outlets (e.g., Society of Environmental Journalists, Mongabay) with the goal of strengthening the
reach and visibility of the research, and increase scientific understanding. The findings of this research
will be valuable to policymakers, the private sector, and civil society organizations tasked with
formulating societal and conservationist responses to the radical transformation that is already changing
the face of the Amazon.
Transformative Nature of Project: The integration of land-change science (LCS) and political ecology
(PE) is seen as key approaches to understanding today’s most pressing environmental problems
(Brannstrom and Vadjunec 2013). LCS has long been dominated by a location rent paradigm focusing on
land managers acting in isolation. The proposed research seeks “optimize” the integration of LCS and PE
by using Bayesian variants of spatial model to understand landscape process triggered by infrastructure
development and expansion of mining and agricultural activities. This has the potential to transform the
integration of land change science by (1) pointing to multiple land change outcomes resulting from a
single process (infrastructure development), and by (2) elaborating this process as one affecting multiple
agents (soybean farmers, small-farmers, and companies investing in NTFP, among others) and
landscapes. Our results will represent an important step in understanding the spatial effects and
implications of infrastructure in market-oriented strategies to conservation, small farmers livelihoods and
protected areas. Our results have the potential to re-direct the ongoing research, funding, and policy that
focuses on the promote these conservation mechanisms.
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Project Timeline
#
Activities
2021
2022
1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
Refine GIS database of infrastructure projects
Collect/sythesize available data for the Basin
Elaborating questionaries
IRB preparation and submission
Secondary data collection
Fieldwork logistical preparation
Fieldwork surveys and key informant interviews
Content Analysis and Organization
Statistical Modelling
Dissertation Writing
Defense
10 Prepare and submit manuscript for publication
1
2
3
4
5
6
7
8
9
10
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Biographical Sketch(es)
Aghane Antunes
a. Professional Preparation
University of Florida
Geography
Ph.D. Student
University of Florida
Geography
M.Sc. 2018
Gama Filho University
Corporate
Communications
Specialization
2010
Syracuse University
International Corporate
Communications
Specialization
2013
Federal University of Maranhão/Rio de
Janeiro University Center (Brazil)
Journalism
B.Sc. 2009
b. Appointments
2017-Present Ph.D. Student and Instructor, Geography, University of Florida
2015-2017
Master Student and Instructor, Geography, University of Florida
2014
Senior Governamental Relations Analyst, Avon Corporation (São Paulo,Brazil)
2011-2014
Institutional & Governmental Relations Analyst, Vale (MaranhãoBrazil)
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2010-2011
Communication Analyst (railway/port expansion), TÜV Rheinland (Maranhão/Brazil)
2008-2009
Environmental, Communications and Institutional Relations Coordinator for Jirau
Hydroelectric project, ESBR (Rio de Janeiro/Rondônia, Brazil)
2006-2008
Communication Analyst/ Institutional Relations Coordinator for Estreito Hydroelectric
project, Clara Comunicação PR Agency/CESTE (Maranhão/Tocantins, Brazil)
2005
Press Relations for Petrobras (port/oil operations), Clara Comunicação PR
Agency/Petrobras (Maranhão, Brazil)
c. Publications
Walker, R.T., Simmons, C.S., Arima, E., Miyoshi, Y., Antunes, A., Waylen, M., Irigaray, M. 2019.
Avoiding Amazonian Catastrophes: Prospects for Conservation in the 21st Century. One Earth.
C.S. Simmons, R. Walker, S. Aldrich, E. Arima, E. Castro, F. Michellotti, M. Waylen, Antunes, A. 2018.
Discipline and Develop: Destruction of the Brazil Nut Forest in the Lower Amazon Basin. Annals of the
Association of American Geographers. 2018.
C. S. Simmons, L. Famolare, M. Macedo, P. Moorecroft, R, T. Walker, M. Coe, E. Arima, D. Valle, R.
Munoz Carpena, B. Scheffers, C. Fraisee, D. Juhn, M. Diniz, M. Diniz, C. Szlafsztein, C. Ruiz, R Pereira,
G. Rocha, O. Canto, 2018, Antunes, A. 2018. Science in Support of Amazonian Conservation in the 21st
Century. Biotropica.
Antunes, A. 2019. Non-Timber Forest Products (NTFP) and the Global Cosmetic Industry: Exploring the
Contributions of NTFP to Rural Livelihoods in the Brazilian Amazon. Thesis for Master of Sciences
Degree in Geography, University of Florida, Department of Geography.
Antunes, A. (forthcoming). Non-Timber Forest Products (NTFP) and the Global Cosmetic Industry:
Exploring the Contributions of NTFP to Rural Livelihoods in the Brazilian Amazon. Land (in review).
d. Synergistic Activities
Instructor, Global and Regional Economies (GEO2500), University of Florida. Fall 2017, 2019; Spring,
Fall 2019, Spring 2020.
Instructor, Economic Geography (GEO3502), University of Florida. Fall 2018, Spring, Fall 2019, Spring
2020.
Instructor, Physical Geography Lab (GEO2200), University of Florida. Fall, Spring, Summer 2016
Co-organizer, 5 Sessions on "Society and Environment in the Amazon 1: People, Policy, and the
Environment”, Annual Meeting of the American Association of Geographers, San Francisco, 2016.
Qualifications of the co-PI: The co-PI is uniquely qualified to lead this research. First, the co-PI have
conducted preliminary work to understand the market-based NTFP extraction in the Amazon, in addition
to collaborate in other three articles exploring the impact of infrastructure development for conservation
in the Amazon, which creates a necessary foundation for the hypotheses that drive this proposal. Second,
the co-PI has worked for several years in private multinational companies with operations in the Brazilian
Amazon, including large-scale hydropower construction and mining, port and railway projects (e.g.,
Estreito and Jirau hydropower dams, Ferro Carajas railway and port expansion). Consequently, the coPI have developed first-hand knowledge about infrastructure and development projects in the Amazon
region. She is also experienced in organize research logistics and schedule the interviews. With this NSF
grant support, the co-PI will visit four sites in the Amazon, estimating 15 days in each site, including
Belem.
e.
Collaborators and Co-Editors
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Simmons, C. (University of Florida), Walker, R.T. (University of Florida), Arima, E. (Michigan State
University)
Budget and Budget Justification
Budget Justification
PROPOSAL
NO.
ORGANIZATION
University of Florida
Gra
nted
Proposed
PRINCIPAL INVESTIGATOR/PROJECT
DIRECTOR
AWARD
NO.
A. SENIOR PERSONNEL: PI/PD, Co-PI´S, Faculty and Other
Senior Associates
(List each separately with title, A.7. show number in
brackets)
Last
0.
First Name
M
Name
Title
Professor
Cynthia
X
Simmons
PhD
Candidate
1.
Aghane
X
Antunes
) TOTAL SENIOR PERSONNEL (1( 0 6)
B. OTHER PERSONNEL (SHOW NUMBERS IN
BRACKETS)
1.
(
0 ) POST DOCTORAL ASSOCIATES
2.
) OTHER PROFESSIONALS (TECHNICIAN,
(
0 PROGRAMMER, ETC.)
3.
) GRADUATE
(
0 STUDENTS
4.
(
4 ) UNDERGRADUATE STUDENTS
5.
) SECRETARIAL - CLERICAL (IF CHARGED
(
0 DIRECTLY)
6.
(
0 ) OTHER
NSF Funded
0.00
equipment item 1
0.00
Funds
Granted
by NSF
Funds
Person-months
ACA
SU
CAL
D
MR
0.0
0.00
0.00
0
0.0
0
Requested By
Proposer
$0
$0
$0
0.00
0.00
0.00
0.00
TOTAL SALARIES AND WAGES (A+B)
C. FRINGE BENEFITS (IF CHARGED AS
DIRECT COSTS)
TOTAL SALARIES, WAGES AND FRINGE
BENEFITS (A+B+C)
D. PERMANENT EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR
EACH ITEM EXCEEDING $5,000)
0.0
0
0.0
0
$0
$0
$0
$1,000
$0
$0
$1,000
$0
$1,000
$0
TOTAL EQUIPMENT
E. TRAVEL
DURATION
(MONTHS)
$0
1. DOMESTIC (INCL. U.S.
POSSESSIONS)
2. INTERNATI
ONAL
$0
$1,500
F. PARTICIPANT SUPPORT COSTS
1. STIPENDS
2. TRAVEL
$0
$8,100
3. SUBSISTENCE
$0
4. OTHER
$0
18
(
0
) TOTAL NUMBER OF
PARTICIPANTS
$8,100
G. OTHER DIRECT COSTS
1. MATERIALS AND
SUPPLIES
2. PUBLICATION
COSTS/DOCUMENTATION/DISSEMINATION
3. CONSULTANT
SERVICES
4. COMPUTERS
SERVICES
$0
$2,000
$0
$99
5. SUBAWARDS
$0
6. OTHER
$0
TOTAL OTHER DIRECT COSTS
H. TOTAL DIRECT COSTS (A THROUGH G)
I. INDIRECT COSTS (SPECIFY RATE AND
BASE)
Name of indirect cost
item
FirstIndirectCostI
tem
$2,099
$12,699
Amount
$1,000
Rate
52.00
%
520
TOTAL INDIRECT COSTS
J. TOTAL DIRECT AND INDIRECT COSTS
(H+I)
K. SMALL BUSINESS FEE (For further information, see the Small Business
Innovation Research (SBIR) solicitation.)
L. AMOUNT OF THIS REQUEST (J) OR (J
MINUS K)
AGREED LEVEL IF
M. COST SHARING: PROPOSED LEVEL
DIFFERENT $
$520
$13,219
$0
$13,219
$0
Budget Justification
A. SENIOR PERSONNEL
B. OTHER PERSONNEL
4 undergraduate/graduate students from a local federal university ($1,000)
C. FRINGE
D. EQUIPMENT
E. TRAVEL $8,100
International flight $1,500.00 Round-trip airfare, Gainesville-Belem (TAM Airlines)
Lodging $0.00 Staying with my family
Per Diem $3,600 $80/day x 2.5 months (45 days)
Lodging $2,700 $20/day x 2.5 months (45 days) x 3 rooms (undergraduate assisting fieldwork surveys)
Fuel $300
F. PARTICIPANT SUPPORT
G. OTHER DIRECT COST $5,000.00
Materials and supplies
GPS $300.00 Needed for georeferencing field plots
Government documents, photocopies
and survey print outs
$300.00 Purchase of databases and
government documents, photocopies
Consultants
Assistants $1,000.00 Hiring of field assistants to help in
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data collection
Local transportation
Rental car (4x4 pickup truck) $3,200.00 20 days rental of a pickup to visit
locations from where peasants were
displaced or went to after then.
Publications $2,000
Other
Phone credit $100.00 $50/month x 2 months
$13,219
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