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Barbier & Burgess ( [4] ) conducted a vast study on the tropical deforestation of Africa, Asia and Latin America. They studied deforestation by tropical agricultural land expansion. The study encompassed data from 1961 to 1994. They studied both FE and RE models and then added three additional institutional variables: corruption index, property rights index, and political stability index. For all tropical countries, they found income per capita US$ 5445 as a turning point, while for Asia in particular, it was US$ 1815 and for Latin America, US$ 4946.
Cubic models have given optimistic results for EKC in some cases, while most Quadratic models have not. In many observations, deforestation has not shown any supporting evidence for the full trajectory of the EKC ( [67] , [66] , [40] ). The reason for this may be that the per capita income of the observed countries is at the first stage of EKC, when degradation increases with increasing income per capita. According to Koop & Tole ( [40] ), empirical results indicate that a significant EKC exists in the simple regression, but is gradually lost when the conditions are freed up. Tests also strongly indicate that less restrictive specifications are favored by the data. However, Bhattarai & Hammig ( [7] ) conducted another study in Africa with less than optimistic results. They found a peak at income per capita of US$ 5000. However, the cases which were not found proven to have the statistically significant full trajectory of EKC, might be due to presence of income per capita in the first-stage of EKC. In the RE model, lack of incorporating some important determinants might cause the deviation.
In June 2009, the population of the country was about 156 M, with a growth rate of 1.3%. Seventy-seven percent of the total population lives in rural areas ( [78] ). Bangladesh is a country with a developing economy. Economic growth influences urbanization of rural areas in the developing countries ( [13] ). In Bangladesh, total urban population in 2009 was 27.6% and it has been projected to reach at 56.4% in 2050 ( [18] ). It shows a decrease in rural population in 2050. Average annual rate of change of urban population in the period 1975-2009 was 5.15%, which has been projected to reduce at 2.52% in the period 2009-2050. Whereas, average annual rate of change of the rural population has been projected to -0.47% in the period 2009-2050. The rate of urbanization in 1975-2009 was 3.03%, which has been projected to reduce at 1.75% in the period 2009-2050 ( [18] ). With the increase of urban population and the reduction of rural population along with the reduction of urbanization rate in the period 2009-2050, show a long run effect of retarding deforestation. DeFries et al. ( [17] ) also support this phenomenon. It has been recently observed in the neighboring country, India ( [16] ). However, environmentalists are concerned about the present increasing environmental degradation in Bangladesh. The country is under severe threat of climate change and forest biodiversity loss. According to the IPCC and Bangladesh Climate Change Strategy and Action Plan 2008 ( [33] , [51] ), Bangladesh will be among the worst-affected countries of climate change in the world. The macro-economy in Bangladesh can show the movement of environmental degradation through the EKC. The following sections aim at discussing this.
Bangladesh is one of the thirteen countries that have the potential to grow faster in their economy ( [1] ). It has more than tripled its GDP in real terms and food production has increased three-fold ( [51] ). Observing the trend of last twenty years, it is assumed that the country will become a middle-income country by 2020. In three out of the last five years, the economy has grown at 6% and over ( Fig. 5 - [12] ). The economic survey of Bangladesh ( [25] ) states that though a decrease in growth rate has been observed in some years, growth is continuing nonetheless ( Tab. 2 ). For a developing country with this GDP growth rate, Bangladesh is defying the impact of the global economic fallout ( [1] ) and ranked 68 th in World ranking in the CIA World Fact Book ( [12] ). ADB ( [1] ) reported that the global center for economic activity is already being shifted to India, China and other large emerging economies, and that Bangladesh must make all efforts to capitalize on its comparative advantages to benefit from this global paradigm shift ( [26] ).
Fig. 5 - GDP real growth rate of Bangladesh from 2000 to 2008.
Tab. 2 - Growth trend of real Gross Domestic Product (GDP) in Bangladesh during 1975-2000 (at 1984/85 prices).
Year | Real GDP (millions of taka) | Growth Rate (%) |
---|---|---|
1975-76 | 293820 | 5.7 |
1976-77 | 301670 | 2.7 |
1977-78 | 323010 | 7.1 |
1978-79 | 338520 | 4.8 |
1979-80 | 341300 | 0.8 |
1980-81 | 352880 | 3.4 |
1981-82 | 357220 | 1.2 |
1982-83 | 374700 | 4.9 |
1983-84 | 395030 | 5.4 |
1984-85 | 406930 | 3.0 |
1985-86 | 424590 | 4.3 |
1986-87 | 442340 | 4.2 |
1987-88 | 455130 | 2.9 |
1988-89 | 466610 | 2.5 |
1989-90 | 497530 | 6.6 |
1990-91 | 514440 | 3.4 |
1991-92 | 536190 | 4.2 |
1992-93 | 560230 | 4.5 |
1993-94 | 583840 | 4.2 |
1994-95 | 609790 | 4.4 |
1995-96 | 642440 | 5.3 |
1996-97 | 680210 | 5.9 |
1997-98 | 718670 | 5.7 |
1998-99 | 756120 | 5.2 |
1999-2000 (provisional) | 801710 | 6.0 |
Considering the hypothesis along with the global observation of EKC and the growth trend of the national income of Bangladesh, it is now clear that Bangladesh is going to face a severe threat of environmental degradation in the upcoming years or decades. From the studies of EKC in the developing countries, it is assured that environmental complications will be relentless, until the peak point is achieved. However, economic growth and development are also important. The prime task will be to curb the upcoming environmental threats. The urbanization trend of Bangladesh suggests that retarding deforestation cannot be expected immediately. The literature review of the observations of the EKC hypothesis for deforestation in many regions and countries shows that to reach the turning point, Bangladesh needs to go far at its required income per capita. Some cases in which an N-shape EKC existed were also observed. In these cases, halting deforestation occurs for the time being and a subsequent increase in income per capita again degrades the forests. However, if we are to wait for that standard turning point, the forest ecosystem in Bangladesh may be irreversibly degraded. It would be best to follow the alternative routes ( Fig. 3 and Fig. 4 ). Oestreicher et al. ( [56] ) conclude that several surveillance measures with greater funding and proper governance are critical to slowing deforestation. Santilli et al. ( [62] ) and Culas ( [14] ) confirm that adequate funding of programs for enforcing environmental legislation, finding alternative livelihoods for the forest-dependent people, and alternatives to massive forest clearing and capacity building for dealing with the remote forest regions are critical to reducing deforestation. Over-population indirectly results in deforestation and forest degradation due to poverty ( [61] ). Some economic mechanisms can transform this poverty and peoples’ attitude, which can in turn reduce deforestation. To this end, this paper suggests that Clean Development Mechanism (CDM) and Reducing Emissions from Deforestation and forest Degradation (REDD+) can work towards forest transition. However, this paper assumes that CDM and REDD+ are only parts of a whole forest transition process in Bangladesh, which this paper focuses on. These two mechanisms can be useful to construct an alternative path in the EKC in Bangladesh. The following sections brief on these mechanisms.
Article 12 of the Kyoto Protocol introduces the CDM, originally a part of AIJ (Activities Implemented Jointly). CDM projects typically involve Annex I Parties as investors and Non-Annex I Parties as hosts, and are essentially joint ventures between developed and developing countries. Emission reductions resulting from these projects, beginning in the year 2000, count towards satisfying an Annex-I Party’s obligations to reduce aggregate emissions during the years 2008 to 2012 (first commitment period).
Silveira ( [69] ) discusses the role of CDM in respect to sustainable development, formation of carbon markets, and promotion of bioenergy options. His study concludes that bioenergy projects are attractive and CDM provides a complementary bridge for international cooperation towards sustainable development. Sustainable forest production is at the core of the afforestation/reforestation CDM projects ( [38] ). In this respect, plantation with CDM projects can work better as the source of bioenergy production, which will ultimately reduce the rate of deforestation. Ravindranath et al. ( [57] ) and Reddy & Balachandra ( [58] ) conclude that a woodfuel stove project with the improvement of traditional stoves can be put on the international “carbon market” at competitive cost for GHG emission reduction. They also confirmed that improved cooking stoves would release pressure on the forests. Teixeira et al. ( [74] ), for three A/R CDM projects developed in Brazil, demonstrate that CDM projects have a significant potential impact on local and rural development in Brazil. They have the potential to promote the sustainable use of forestry and soil resources. Klooster & Masera ( [39] ) argue for Mexico that adequately designed and implemented community forestry management projects (proposed as CDM project) can avoid deforestation and restore forest cover and forest density. They comprise promising options for providing both carbon mitigation and sustainable rural development. However, forest management and conservation (slowing deforestation) as well as carbon sequestration in agriculture are not allowed in the first commitment period of the CDM. CDM projects are expected to usher in sustainable development in the Non-Annex I Parties. The development must be in the social, environmental and economic arena of a country. The possible carbon sequestration, biomass combustion efficiency and carbon substitution projects are expected to impact the overall well-being of the host country in many ways.
Receiving GHG benefits from the slowing deforestation, the 2007 COP (Conference of the Parties) 13 in Bali made reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) a central topic of discussion. The same was true of the 2008 COP 14 in Poznan. The mechanism has not come into force yet, as negotiations are ongoing. However, it is expected that REDD+ will be the central forestry activities (slowing deforestation) in the tropical developing countries after 2012 ( [71] ). The financial incentives for REDD+ in the pilot projects established in tropical and sub-tropical areas of Asia, Africa and South America have been found to alter the drivers of land use changes by reducing opportunity costs of retaining forest cover, and are often promoted as multifaceted solutions that not only generate profits and reduce carbon emissions, but also provide benefits for human development and biodiversity ( [9] ). India and Costa Rica have already had success with programs to restore their forests and they feel they should receive compensation for these early conservation efforts ( [76] ). The Democratic Republic of the Congo has large areas assigned to logging concession and is keen for REDD+ to support sustainable forest management ( [77] ). Stickler et al. ( [73] ) found that nations in the Amazon region can potentially participate in REDD+ by slowing clear-cutting of mature tropical forests, slowing or decreasing the impact of selective logging, promoting forest regeneration and restoration, and expanding afforestation/reforestation. Possible REDD+ program interventions in a large-scale Amazon landscape indicate that even modest flows of forest carbon funding can provide substantial co-benefits for aquatic ecosystems, but that the functional integrity of the landscape’s myriad small watersheds would be best protected under a more even spatial distribution of forests. As ecosystem services derived from REDD+ projects will have a global interest, it could access a large pool of global stakeholders willing to pay to maintain carbon in forests. Calling for low-biomass Indian forests, Singh ( [70] ) confirms that appropriately designed community-based forest management under REDD+ can provide a means to sustain and strengthen community livelihoods and at the same time avoid deforestation, restore forest cover and density, provide carbon mitigation and create rural assets.
However, before adopting REDD+ as an effective deforestation-reduction mechanism, decisions on the nature of carbon buyers and sellers, financing mode, compensation scheme, and type of land use to be targeted should be made ( [56] ). However, good governance and political will are also important to make this program successfull ( [48] ).
Bangladesh, a non-Annex I Party, ratified the Kyoto Protocol on 22 October 2001. Therefore, Bangladesh is eligible to be a host country for CDM and the expected REDD+ activities. Furthermore, Bangladesh signed the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in 1973; UNFCCC in 1992; and the Convention on Biological Diversity (CBD) in 1992. It is a signatory to the Ramsar Convention and the World Heritage Convention. The Bangladesh Wildlife (preservation) Act, 1974; the Forest Act, 1927 (amended in 1989); the Fish Act, 1950; and the Environment Protection Act, 1995, provide legal support for forest and biodiversity conservation in Bangladesh. The present “National Forest Policy 1994” also supports the mass reforestation activities throughout the country. However, it is necessary to adjust or pinpoint the objectives of the forest policy, national renewable energy policy, and national energy policy, all of which should be compliant with the biodiversity conservation of the forests and thus reduce GHGs.
Although the present national forest policy covers retarding deforestation and biodiversity conservation ( [52] ), it does not have any openings for accepting economic flexible mechanisms like CDM and REDD+. In the global climate-change perspective, Bangladesh forest policy should be reoriented to mitigate the climate change retarding deforestation. The present “Renewable Energy Policy 2008” of Bangladesh has an important objective of promoting clean energy for CDM ( [27] ), but there are no strong guidelines for CDM activities. As the CDM forest can give birth to huge carbon credit ( [69] ), the attitudes of the rural peoples can be altered towards maintaining the sustainability of the forest biomass through the encouragement of small-scale CDM in the homestead forests. The present renewable energy policy has marked the importance of biomass for producing electricity through biomass gasification. This importance can be linked with CDM. As carbon sequestration and carbon substitution are the most important approaches for mitigating climate change ( [68] ), sustainable production of biomass and its conversion to secondary clean energy, i.e. , electricity, can be useful for both the economic development of rural livelihoods and environmental amelioration. The most useful form of commercial energy is electricity, which can be produced from both renewable and non-renewable resources. The present “National Energy Policy (Draft), 2008” should emphasize the use of renewable resources for producing electricity. Of these renewables, biomass has the added advantage of being able to be set up on a small scale to provide power and electricity to villages and small clusters or on a large scale for electrical power generation to be fed to the national grid. Thus, there is a need to produce woody biomass not only as fuel but also as a means to address climate change-related issues and socio-economic problems.
To retard the deforestation/degradation of the forestlands, governance is a key issue ( [68] ). The elimination of corruption in the forest department and ensuring political commitment to preserving the forests is vital in order to achieve the effective implementation of policy and strategies. Governance in the arena of bridging gaps between policy, science and practice, is also important. Various regulatory policies and measures in force in the country are often too vague to be of much use in actual practice and leave a great deal of scope for interpretation and therefore their abuse through legal loopholes. These policies, rules and regulations should therefore be examined closely for such loopholes. Sufficient explanatory clarifications should be provided and guidelines should be more clearly laid down. A case in point is the national energy policy needing to take the issue of GHG mitigation more seriously. Resolution of intersectoral conflicts among the forestry, agriculture, environment, land, wildlife and energy sectors is another important governance issue. There is a serious gap in terms of coordination between economic and environmental objectives. The gap is more serious in the case of the understanding and coordination of the linkages between GHG abatement activities and measures. Filling this gap is of immense importance for retarding deforestation through the undertaking of CDM and REDD+ activities in Bangladesh.
A literature review shows a significant number of cases proving the EKC trajectories for deforestation. However, this study found higher per capita income as the turning point. The trend of economic growth and urbanization suggests that Bangladesh has far to go before it may reach this turning point where deforestation will be retarded. Hence, the study supports its hypothesis that Bangladesh is presently at the initial up-facing stage of EKC for deforestation. However, the economy of Bangladesh is growing. In order for the turning point for halting deforestation in Bangladesh to be shortened, a tunnel in the EKC has to be made. The discussions show that CDM and REDD+ can be effective mechanisms for making this tunnel. Reorientation of the national forest policy, national renewable energy policy and national energy policy would be favorable for retarding deforestation in Bangladesh. Furthermore, good governance in the country has been emphasized as a vital component in the development of deforestation-halting activities. The findings of this study would be relevant for both forestry development in Bangladesh and global climate change mitigation.
The authors sincerely acknowledge the support and assistance provided by the Bangladesh Forest Department, Bangladesh, and Bangladesh Bureau of Statistics, during data collection. We also greatly acknowledge the anonymous reviewers for their valuable comments, criticism and suggestion to improve the paper.
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Miah MD, Masum MFH, Koike M, Akther S (2011). A review of the environmental Kuznets curve hypothesis for deforestation policy in Bangladesh. iForest 4: 16-24. - doi: 10.3832/ifor0558-004
Received: Aug 13, 2010 Accepted: Dec 13, 2010
First online: Jan 27, 2011 Publication Date: Jan 27, 2011 Publication Time: 1.50 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2011
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deforestation , the clearing or thinning of forests by humans. Deforestation represents one of the largest issues in global land use . Estimates of deforestation traditionally are based on the area of forest cleared for human use, including removal of the trees for wood products and for croplands and grazing lands. In the practice of clear-cutting , all the trees are removed from the land, which completely destroys the forest . In some cases, however, even partial logging and accidental fires thin out the trees enough to change the forest structure dramatically.
Conversion of forests to land used for other purposes has a long history. Earth’s croplands , which cover about 49 million square km (18.9 million square miles), are mostly deforested land. Most present-day croplands receive enough rain and are warm enough to have once supported forests of one kind or another. Only about 1 million square km (390,000 square miles) of cropland are in areas that would have been cool boreal forests , as in Scandinavia and northern Canada . Much of the remainder was once moist subtropical or tropical forest or, in eastern North America , western Europe, and eastern China , temperate forest .
The extent to which forests have become Earth’s grazing lands is much more difficult to assess. Cattle or sheep pastures in North America or Europe are easy to identify, and they support large numbers of animals. At least 2 million square km (772,204 square miles) of such forests have been cleared for grazing lands. Less certain are the humid tropical forests and some drier tropical woodlands that have been cleared for grazing. These often support only very low numbers of domestic grazing animals, but they may still be considered grazing lands by national authorities. Almost half the world is made up of “ drylands ”—areas too dry to support large numbers of trees—and most are considered grazing lands. There, goats , sheep , and cattle may harm what few trees are able to grow.
Although most of the areas cleared for crops and grazing represent permanent and continuing deforestation, deforestation can be transient . About half of eastern North America lay deforested in the 1870s, almost all of it having been deforested at least once since European colonization in the early 1600s. Since the 1870s the region’s forest cover has increased, though most of the trees are relatively young. Few places exist in eastern North America that retain stands of uncut old-growth forests.
The United Nations Food and Agriculture Organization (FAO) estimates that the annual rate of deforestation is about 1.3 million square km per decade, though the rate has slowed in some places in the early 21st century as a result of enhanced forest management practices and the establishment of nature preserves. The greatest deforestation is occurring in the tropics, where a wide variety of forests exists. They range from rainforests that are hot and wet year-round to forests that are merely humid and moist, to those in which trees in varying proportions lose their leaves in the dry season, and to dry open woodlands. Because boundaries between these categories are inevitably arbitrary, estimates differ regarding how much deforestation has occurred in the tropics.
A major contributor to tropical deforestation is the practice of slash-and-burn agriculture , or swidden agriculture ( see also shifting agriculture ). Small-scale farmers clear forests by burning them and then grow crops in the soils fertilized by the ashes. Typically, the land produces for only a few years and then must be abandoned and new patches of forest burned. Fire is also commonly used to clear forests in Southeast Asia , tropical Africa, and the Americas for permanent oil palm plantations.
Additional human activities that contribute to tropical deforestation include commercial logging and land clearing for cattle ranches and plantations of rubber trees , oil palm , and other economically valuable trees.
The Amazon Rainforest is the largest remaining block of humid tropical forest, and about two-thirds of it is in Brazil . (The rest lies along that country’s borders to the west and to the north.) Studies in the Amazon reveal that about 5,000 square km (1,931 square miles) are at least partially logged each year. In addition, each year fires burn an area about half as large as the areas that are cleared. Even when the forest is not entirely cleared, what remains is often a patchwork of forests and fields or, in the event of more intensive deforestation, “islands” of forest surrounded by a “sea” of deforested areas.
The commercial palm oil industry rapidly expanded in the late 20th century and led to the deforestation of significant swaths of Indonesia and Malaysia as well as large areas in Africa. New plantations are often formed using slash-and-burn agricultural methods, and the resulting fragmentation of natural forests and loss of habitat threatens native plants and animals. Bornean and Sumatran orangutans are especially iconic species threatened by the expansion of oil palm farming in Indonesia.
Deforested lands are being replanted in some areas. Some of this replanting is done to replenish logging areas for future exploitation, and some replanting is done as a form of ecological restoration , with the reforested areas made into protected land. Additionally, significant areas are planted as monotypic plantations for lumber or paper production. These are often plantations of eucalyptus or fast-growing pines —and almost always of species that are not native to the places where they are planted. The FAO estimates that there are approximately 1.3 million square km (500,000 square miles) of such plantations on Earth.
Many replanting and reforestation efforts are led and funded by the United Nations and nongovernmental organizations. However, some national governments have also undertaken ambitious replanting projects. For example, starting in 2017, the government of New Zealand sought to plant more than 100 million trees per year within its borders, but perhaps the most ambitious replanting project took place in India on a single day in 2017, when citizens planted some 66 million trees.
Conventional understanding, an atmospheric moisture pump, evaporation and forests, rainfall transects, seasonal rainfall, spatial contexts and switching states, the search for further evidence, new investigations, acknowledgments, references cited.
Douglas Sheil (e-mail: [email protected] or [email protected] ) is with the Institute of Tropical Forest Conservation, Mbarara University of Science and Technology, in Kabale, Uganda. He and Daniel Murdiyarso are with the Center for International Forestry Research in Jakarta, Indonesia.
Douglas Sheil, Daniel Murdiyarso, How Forests Attract Rain: An Examination of a New Hypothesis, BioScience , Volume 59, Issue 4, April 2009, Pages 341–347, https://doi.org/10.1525/bio.2009.59.4.12
A new hypothesis suggests that forest cover plays a much greater role in determining rainfall than previously recognized. It explains how forested regions generate large-scale flows in atmospheric water vapor. Under this hypothesis, high rainfall occurs in continental interiors such as the Amazon and Congo river basins only because of near-continuous forest cover from interior to coast. The underlying mechanism emphasizes the role of evaporation and condensation in generating atmospheric pressure differences, and accounts for several phenomena neglected by existing models. It suggests that even localized forest loss can sometimes flip a wet continent to arid conditions. If it survives scrutiny, this hypothesis will transform how we view forest loss, climate change, hydrology, and environmental services. It offers new lines of investigation in macroecology and landscape ecology, hydrology, forest restoration, and paleoclimates. It also provides a compelling new motivation for forest conservation.
Life depends on Earth's hydrological cycle, especially the processes that carry moisture from oceans to land. The role of vegetation remains controversial. Local people in many partially forested regions believe that forests “attract” rain, whereas most modern climate experts would disagree. But a new hypothesis suggests that local people may be correct.
The world's hydrological systems are changing rapidly. Food security in many regions is heavily threatened by changing rainfall patterns ( Lobell et al. 2008 ). Meanwhile, deforestation has already reduced vapor flows derived from forests by almost five percent (an estimated 3000 cubic kilometers [km 3 ] per year of a global terrestrial derived total of 67,000 km 3 ), with little sign of slowing ( Gordon et al. 2005 ). The need for understanding how vegetation cover influences climate has never been more urgent.
Makarieva and Gorshkov have developed a hypothesis to explain how forests attract moist air and how continental regions such as the Amazon basin remain wet ( Makarieva et al. 2006 , Makarieva and Gorshkov 2007 , and associated online discussions; hereafter, collectively “Makarieva and Gorshkov”). The implications are substantial. Conventional models typically predict a “moderate” 20 to 30 percent decline in rainfall after continental-scale deforestation ( Bonan 2008 ). In contrast, Makarieva and Gorshkov suggest that even relatively localized clearing might ultimately switch entire continental climates from wet to arid, with rainfall declining by more than 95 percent in the interior.
Whereas Makarieva and Gorshkov's publications are technical, detailing the physics behind their hypothesis, we explain the basic ideas and their significance for a wider audience. We begin by noting why the ideas are credible and merit notice. We then summarize the conventional understanding of forest-climate interactions and Makarieva and Gorshkov's proposals. We focus on tropical forests. After examining what makes these forests special, we consider various implications and research opportunities related to Makarieva and Gorshkov's hypothesis. Finally, we underline the importance of these ideas for forest conservation.
Despite considerable research, the mechanisms determining global climate remain poorly understood. Any consensus summary on climate physics must spend more words on detailing uncertainties than on facts (e.g., IPCC 2007 ). Despite recognized advances in recent decades, not all key insights are immediately noted among the thousands of published articles. Makarieva and Gorshkov's work, which focuses on the equations of atmospheric behavior, appears to have been unjustly ignored. Our own assessment, as well as that of expert colleagues with whom we have consulted, is that Makarieva and Gorshkov's hypothesis is interesting and important. It must now be scrutinized and evaluated.
Deforestation has been implicated as contributing to declining rainfall in various regions (including the Sahel, West Africa, Cameroon, Central Amazonia, and India), as well as to weakening monsoons ( Fu et al. 2002 , Gianni et al. 2003 , Malhi and Wright 2005 ). But the links remain uncertain.
Observations suggest that extensive deforestation often reduces cloud formation and rainfall, and accentuates seasonality ( Bonan 2008 ). Forest clearings can cause a distinct, convection-driven “vegetation breeze” in which moist air is drawn out of the forest ( Laurance 2005 ). Atmospheric turbulence resulting from canopy roughness and temperature-driven convection are thought to explain the localized increase in rainfall sometimes associated with fragmented forest cover ( Bonan 2008 ).
Because opportunities for experimental investigations are limited, climate researchers rely heavily on simulation models to advance their understanding. Most modern models imply a local decline in rainfall after deforestation, along with regional and even intercontinental climate impacts ( Bonan 2008 ). For climate modelers, key changes associated with deforestation are reduced leaf-area index, rooting depth, canopy roughness and roughness length (measures that influence air flow), and higher albedo (reflectivity). But these changes, their interactions and influences, and their dependence on contexts and scales are understood only in broad terms. Many uncertainties remain, especially about the influence of evaporation, convection, cloud development, and aerosols and land cover, and about how changes in cloud cover translate into changes in rainfall ( IPCC 2007 ).
Atmospheric moisture originates from oceanic and terrestrial evaporation. Rain derived from terrestrial sources and contributing to local rainfall is termed “recycled.” Conventional explanations of wet continental interiors emphasize such recycling—but do the numbers add up?
The proportion of recycled rain, a measure dependent on the extent of the area considered, shows little consistent difference between wet and dry regions: an estimated 25 to 60 percent in the Amazon (e.g., Marengo 2005 ), 28 percent in the Nile region ( Mohamed et al. 2005 ), more than 50 percent for summer rain in the midwestern United States ( Bosilovich and Schubert 2002 ), and more than 90 percent for the Sahel ( Savenije 1995 ). What is puzzling about wet regions is not the proportion of recycling, but the question of what drives the inward flows of atmospheric moisture required to replace what flows out through rivers ( Savenije 1996 ).
Conventional theory offers no clear explanation for how flat lowlands in continental interiors maintain wet climates. Makarieva and Gorshkov show that if only “conventional mechanisms” (including recycling) apply, then precipitation should decrease exponentially with distance from the oceans. Researchers have previously puzzled over a missing mechanism to account for observed precipitation patterns ( Eltahir 1998 ). Makarieva and Gorshkov's hypothesis offers an elegant solution: they call it a “pump.”
Pressure gradients driven by temperature and convection are considered to be the principle drivers of air flows in conventional meteorological science. Makarieva and Gorshkov argue that the importance of evaporation and condensation has been overlooked.
Makarieva and Gorshkov draw attention to the fact that under typical atmospheric conditions, the partial pressure of water vapor near the earth's surface greatly exceeds the weight of the water held in the atmosphere above it. They argue that this imbalance can generate powerful airflows. Force results from the way temperature and pressure both decline with altitude in the troposphere (lower atmosphere). When the vertical temperature decline (the “lapse rate”) is less than the critical value of 1.2 degrees Celsius (°C) per km, atmospheric water can remain static and in a gaseous state. But the global average lapse rate is more than 6°C per km. At these higher rates, water vapor rises and condenses. The reduction in atmospheric volume that takes place during this gas-to-liquid phase change causes a reduction in air pressure. This drop in pressure has routinely been overlooked.
Air currents near Earth's surface flow to where pressure is lowest. According to Makarieva and Gorshkov, these are the areas that possess the highest evaporation rates. In equatorial climates, forests maintain higher evaporation rates than other cover types, including open water. Thus, forests draw in moist air from elsewhere; the larger the forest area, the greater the volumes of moist air drawn in (see figure 1 ). This additional moisture rises and condenses in turn, generating a positive feedback in which a large proportion of the water condensing as clouds over wet areas is drawn in from elsewhere. The drivers (solar radiation) and basic thermodynamic concepts and relationships are the same as in conventional models, thus most behaviors are identical—the difference lies in how condensation is incorporated.
Makarieva and Gorshkov's “biotic pump.” Atmospheric volume reduces at a higher rate over areas with more intensive evaporation (solid vertical arrows, widths denotes relative flux). The resulting low pressure draws in additional moist air (open horizontal arrows) from areas with weaker evaporation. This leads to a net transfer of atmospheric moisture to the areas with the highest evaporation. (a) Under full sunshine, forests maintain higher evaporation than oceans and thus draw in moist ocean air. (b) In deserts, evaporation is low and air is drawn toward the oceans. (c) In seasonal climates, solar energy may be insufficient to maintain forest evaporation at rates higher than those over the oceans during a winter dry season, and the oceans draw air from the land. However, in summer, high forest evaporation rates are reestablished (as in panel a). (d) With forest loss, the net evaporation over the land declines and may be insufficient to counterbalance that from the ocean: air will flow seaward and the land becomes arid and unable to sustain forests. (e) In wet continents, continuous forest cover maintaining high evaporation allows large amounts of moist air to be drawn in from the coast. Not shown in diagrams: dry air returns at higher altitudes, from wetter to drier regions, to complete the cycle, and internal recycling of rain contributes significantly to continental-scale rainfall patterns. Source: Adapted from ideas presented in Makarieva and Gorshkov (2007) .
Makarieva and Gorshkov's estimates, incorporating volume changes from condensation, imply that when forest cover is sufficient, enough moist air is drawn in to maintain high rainfall inside continents. The numbers now add up: thus, condensation offers a mechanism to explain why continental precipitation does not invariably decline with distance from the ocean.
We distinguish two types of evaporation. Transpiration is the evaporation flux from within plants; plants determine this flow by controlling their stomata (pores on leaves and other surfaces). Evaporation from wet surfaces, soils, and open water is also important. Which pathway contributes most to overall evaporation depends on conditions ( Calder 2005 , Savenije 2004 ).
Forests evaporate more moisture than other vegetation, typically exceeding flux from herbaceous cover by a factor of 10 ( Calder 2005 ). Closed tropical forests typically evaporate more than a meter of water per year ( Gordon et al. 2005 ). Some evaporate more than two meters ( Loescher et al. 2005 ).
Forest evaporation benefits from canopy height and roughness, which leads to turbulent airflows. This has been termed the “clothesline effect,” as it is the same reason laundry dries more quickly on a line than when laid flat on the ground ( Calder 2005 ). If moisture is sufficient, forest evaporation is constrained principally by solar radiation and weather ( Calder et al. 1986 , Savenije 2004 ). Large tropical trees can transpire several hundred liters of water each day ( Goldstein et al. 1998 ).
Water reserves are important. Plants with high stem volumes allow transpiration to outstrip root uptake, as stem water reserves are depleted by day and replenished at night ( Goldstein et al. 1998 , Sheil 2003 ). Trees (and forest lianas) typically have deeper roots than other vegetation and can thus access subterranean moisture during droughts ( Calder et al. 1986 , Nepstad et al. 1994 ). Many forest soils possess good water infiltration and storage—properties often lost with deforestation ( Bruijnzeel 2004 ). Vertical translocation of soil water through the forest soil profile by roots at night may also be important ( Lee et al. 2005 ). In some sites—notably, cloud forests and forests subjected to coastal fogs—abundant bryophytes and dense foliage contribute to efficient mist and dew interception ( Dietz et al. 2007 ).
Makarieva and Gorshkov suggest that forests can influence when rain falls. Precipitation occurs once condensed moisture has accumulated and the buoyancy generated by rising humid air is low enough. They note that evaporation declines when plants close their stomata, as often occurs in the latter half of the day to alleviate moisture stress ( Pons and Welschen 2004 ). This decline may help explain why most tropical rain falls after midday in many terrestrial (but not in marine) settings ( Nesbitt and Zipser 2003 ). This prediction requires investigation.
Makarieva and Gorshkov's hypothesis predicts two types of coast to continental interior rainfall trends (following a transect path perpendicular to the regional isohyets [contours of long-term rainfall averages]; Savenije 1995 ). They propose and demonstrate that, regardless of location and seasonality, forest-free transects show a near-exponential reduction in annual rainfall with increasing distance from the coast, while well-forested transects show none ( figure 2 ).
How rainfall (precipitation in meters) varies with increasing distance (in kilometers) inland in three forested (A, B, C) and six nonforested (D, E, F, G, H, I) regions. The map shows approximate locations, while the graph shows the best-fit trend lines ( P == P 0 e b × dist , where P is precipitation, e is the base of natural logarithms, dist is distance, P 0 is precipitation at dist == 0, and b is a constant that expresses rate of decline). These fall into two groups: (1) the near-linear (gently rising) forested transects (green), and (2) the near-exponentially declining nonforested transects (orange). Source: Data derived and replotted from Makarieva and Gorshkov (2007) .
Global climate models may fit these rainfall patterns, but they do not predict them. This is an important distinction. As Makarieva and Gorshkov note, “it is widely admitted that the modern representation of atmospheric convection in GCMs [global circulation models] is a parameterization, not a theory.”
How does Makarieva and Gorshkov's hypothesis apply in the seasonal tropics? These monsoonal climates switch between two states: wet and dry. This switch is driven by the annual rhythm of solar energy outside the equatorial regions and its different impact on land and seas. Rather than a classical temperature-based explanation, in Makarieva and Gorshkov's view, switching is dependent on relative evaporation fluxes. During seasons of reduced solar energy, land evaporates less moisture than does open water (oceanic evaporation remains substantial even in winter) and the seas draw air from the land, leading to a dry season (see figure 1c ). When stronger sunshine returns, solar energy is again sufficient for the land to evaporate more moisture than neighboring seas, causing the swing in air currents that marks the classic monsoons. The switching depends on the positive feedbacks involved in the evaporation-rainfall system.
Not all seasonal shifts in tropical rainfall are similar, however. Much of tropical South America experiences a prolonged dry season—but without a clear switching of air currents flowing to and from the coast ( Zhou and Lau 1998 ). Notably, vast areas of these forests remain green through the dry season by accessing deep soil moisture reserves that are replenished each wet season ( Juarez et al. 2007 , Myneni et al. 2007 ). The resulting dry-season evaporation does not wholly overcome the influence of lower air pressure at sea, but according to Makarieva and Gorshkov, it can keep the difference small and increase the likelihood of terrestrial rain.
In Makarieva and Gorshkov's hypothesis, wet seasons can start sooner if they are preceded by high land-based evaporation, and can begin later (or not at all) if evaporation is low. This prediction is consistent with observations in southern Amazonia, where severe drought reduces the ability of vegetation to transpire and delays the onset of the wet season ( Fu and Li 2004 ). Forest loss and diminished evaporation can thus reduce the penetration of monsoon rains and reduce the duration of the wet season.
Makarieva and Gorshkov's ideas agree with, but go well beyond, conventional climate models that imply that landlocked climatic systems, being less buffered by oceans, are more vulnerable to land-cover change than are coastal areas ( Zhang et al. 1996 ), while forest loss in coastal regions typically has a wider climatic impact ( van der Molen et al. 2006 ). According to Makarieva and Gorshkov, if the near-continuous forest needed to convey moist air from coasts to continental interiors is severed, the flow of atmospheric moisture stops. Thus, clearing a band of forest near the coast may suffice to dry out a wet continental interior. Further, clearing enough forest within the larger forest zone may switch net moisture transport from ocean-to-land to land-to-ocean, leaving any forests remnants to be desiccated. Clearly, such risks need to be assessed and understood.
As an illustration, Makarieva and Gorshkov propose that a forested Australia was “switched” to desert by prehistoric settlers. Aboriginal burning reduced coastal forests, leading to continental desiccation. Is this credible? The jury remains out. Humans arrived in Australia during the last glacial period, when much of the world was drier than it is now. Certainly Australia has been well forested in the past, but, then again, dry episodes have occurred before human arrival ( Morley 2000 ).
Where else, aside from the transect data and the timing of monsoons, might we seek evidence for or against Makarieva and Gorshkov's hypothesis? Presumably, in deep continental interiors surrounded by disappearing forest the pattern would be ideal. Unfortunately, where good long-term data on rain and forest are available, they are from coastal regions, where marine climates prevail, and in mountainous regions, where rainfall is governed by terrain. The widely quoted observation that a century of rainfall records in the now heavily deforested foothills of Karnataka, southern India, is associated with only a minor decline in annual rain days is thus not very illuminating ( Meher-Homji 1980 ).
Data on climatic variability may be more revealing: Makarieva and Gorshkov's hypothesis suggests that forest loss will be associated with a loss of stabilizing feedbacks and increased climatic instability. In Brazil's Atlantic Forest just such a correlation has been detected between reduced tree cover and increased local interannual variation in rainfall ( Webb et al. 2005 ).
Makarieva and Gorshkov's hypothesis has implications for many different fields. We briefly consider some.
Makarieva and Gorshkov's prediction and demonstration of distinct rainfall patterns over forests and nonforested transects are persuasive. But these are generalizations: they ignore variations in landform and cover types within each transect, and the influence of air circulation patterns (the ideal transect direction varies through the year). They do not predict the behavior of moist air over mixed forest/nonforest transects—the regions where forest cover is often disappearing fastest. Satellite observations (e.g., Wang et al. 2009 ) and various existing data, such as those from the International Geosphere Biosphere Programme transects, may shed more light on these patterns (see www.igbp.kva.se ). Along with more field data, local and regional simulators are required in which mechanisms, scenarios, and consequences can be explored.
Hydrological trade-offs in modified landscapes are scale dependent. In the standard view, well verified by field data, a marked reduction of forest canopy results in less water lost to evaporation and increased local runoff ( Calder 2005 ). In contrast, Makarieva and Gorshkov's hypothesis suggests that water evaporated by forests is typically returned with interest, so we would expect a decline in rainfall, leading to lower runoff over a wider region, if forests are depleted.
The role of fire damage in forest degradation is an established positive feedback: once a forest has already burned or been otherwise disturbed and damaged, it becomes more flammable and thus more likely to burn again ( Laurance 2005 ). Makarieva and Gorshkov's hypothesis adds drought to this cycle. Fire damages the properties that keep forests moist and nonflammable—the same properties that drive Makarieva and Gorshkov's pump. Fire reduces leaf area and the root densities responsible for hydraulic lift, and thus weakens the ability of the vegetation to maintain understory humidity. Reduced evaporation in turn reduces rainfall, leading to increased droughts, greater flammability, and increased fire risk—thus adding an additional and unwelcome positive feedback in the degradation cycle.
Makarieva and Gorshkov's hypothesis raises questions regarding the role of feedbacks in landscape ecology. For example, the most competitive leaf phenological behavior is dependent on the climate. Among trees, evergreen foliage is favored by high seasonal unpredictability and also by low seasonal variation in moisture availability, while deciduous foliage is favored by intense and extended droughts as well as by seasonal predictability ( Givnish 2002 ). In addition, some deciduous trees flush (i.e., produce new leaves) well before—and some only after—the rains come, with the former favored in more predictable seasonal contexts and the latter in more irregular conditions. Makarieva and Gorshkov's hypothesis implies that these behaviors, by affecting the rates of evaporation, will influence climate. In monsoon regions, evergreen and early-flushing deciduous vegetation encourage the dry season to end sooner and more regularly, whereas late-flushing deciduous forests experience longer dry seasons. Applying Makarieva and Gorshkov's hypothesis, we expect that these phenological behaviors favor the climatic conditions to which they are best adapted.
But not all feedbacks are necessarily positive. For example, evergreen lianas make up a significant proportion of the canopy in many seasonal tropical forests, where their dominance appears favored by the long dry season ( Schnitzer 2005 ). Any resulting increases in rainfall should favor the trees over the lianas.
Have forests evolved to generate rain? This idea touches on the much-debated possibilities of emergent self-stabilizing behavior (or “Gaia”; e.g., Lenton and van Oijen 2002 ). Trees and forests have evolved numerous times in Earth's history, suggesting a repeated trend to generate rich, self-watering terrestrial habitats. As the previous discussions illustrate, there is scope for self-stabilizing interactions to arise (see also Makarieva and Gorshkov 2007 ). But, as the properties required for an effective forest pump also benefit the individual trees, it appears that any pump emerges as an evolutionary consequence of individual-level competition—it increases forest extent, but this is not why it evolved.
Makarieva and Gorshkov's hypothesis, with its climate switch, provides new twists to old controversies. Human arrival in previously uninhabited regions over the last 50,000 years is invariably associated with extinctions, especially among larger fauna (as in the Australia example mentioned above). The concurrent role of climate change, viewed as a natural phenomenon, continues to be debated ( Koch and Barnosky 2006 ). If severe climate impacts could plausibly result from ancient, human-induced habitat changes, then the sequence of events will need to be reassessed in this framework.
Makarieva and Gorshkov's hypothesis does not tell us how forests can become reestablished after the catastrophic events that punctuate Earth's history ( Morley 2000 ). This question will require us to unravel the feedback processes and thresholds that operate spatially at different scales, and the influences that act upon them. Certainly the hypothesis does not argue that such greenings cannot occur. Presumably, a forest can establish even in a wet coastal site where rainfall declines exponentially with distance from the coast, and it can advance progressively inland, drawing moist air with it. Makarieva and Gorshkov's hypothesis may clarify how South America, but not Africa, managed to maintain large-scale, wet interior climates through past glacials. Perhaps in Africa the presence of large herbivores, and ancestral humans with fire, influenced the balance between forest and nonforest vegetation reducing stability and allowing the climate to switch.
In contrast to Makarieva and Gorshkov, who propose that only natural and intact forests can maintain a working atmospheric pump, we suspect that secondary forest and plantations can have desirable evaporation properties (see, e.g., Olchev et al. 2008 ). While the higher flammability of such vegetation suggests a less-wet environment, which in turn implies a less-effective pump, such properties are not inevitable and can be influenced by management. These properties need to be investigated.
Could we one day afforest the world's deserts? Makarieva and Gorshkov's hypothesis suggests we might. Contrary to most conventional models, Makarieva and Gorshkov's calculations imply that once forests are established in these regions, the biotic pump would be powerful enough to water them. Despite the scales, and the inevitable technical and ethical challenges, such projects may become easier to fund and to implement as carbon dioxide concentrations rise ( Brovkin 2002 ).
If Makarieva and Gorshkov's hypothesis proves valid, important questions will remain concerning how the biotic-pump mechanism interacts with other processes to provide a fuller account of local, regional, and global climate. If the hypothesis proves flawed, a mechanism to explain wet continental interiors will still be needed.
Acceptance of the biotic pump would add to the values that society places on forest cover. By raising regional concerns about water, acceptance of Makarieva and Gorshkov's biotic pump demands attention from diverse local actors, including many who may otherwise care little for maintaining forest cover.
We thank Anastassia Makarieva, Victor Gorshkov, Antonio Nobre, Ian Calder, Meine van Noordwijk, Wolfgang Cramer, and three anonymous reviewers for valuable comments. We also thank Claire Miller and Miriam van Heist for editorial suggestions, and the CIFOR Library and Wageningen Library for locating references. D. S. was supported by an European Commission grant to the Center for International Forestry Research, and by Wildlife Conservation Society support to the Institute of Tropical Forest Conservation.
Bonan GB . 2008 . Forests and climate change: Forcing feedbacks and the climate benefits of forests . Science 320 : 1444 – 1449 .
Google Scholar
Bosilovich MG Schubert SD . 2002 . Water vapor tracers as diagnostics of the regional hydrologic cycle . Journal of Hydrometeorology 3 : 149 – 165 .
Brovkin V . 2002 . Climate-vegetation interaction . Journal de Physique IV 12 : 57 – 72 .
Bruijnzeel LA . 2004 . Hydrological functions of tropical forests: Not seeing the soil for the trees? Agriculture Ecosystems and Environment 104 : 185 – 228 .
Calder IR . 2005 . The Blue Revolution: Land Use and Integrated Water Resources Management . 2nd ed. London : Earthscan .
Calder IR Wright IR Murdiyarso D . 1986 . A study of evaporation from tropical rain forest—West Java . Journal of Hydrology 89 : 13 – 31 .
Dietz J Leuschner C Holscher D Kreilein H . 2007 . Vertical patterns and duration of surface wetness in an old-growth tropical montane forest, Indonesia . Flora 202 : 111 – 117 .
Eltahir EAB . 1998 . A soil moisture–rainfall feedback mechanism, 1: Theory and observations . Water Resources Research 34 : 765 – 776 .
Fu C Harasawa H Kasyanov V Kim J-W Ojima D Wan Z Zhao S . 2002 . Regional-global interaction in East Asia . Pages 109 – 149 in Tyson P Fun C Fuchs R Lebel L Mitra AP Odada E Perry J Steffen W Virji H , eds. Global-Regional Linkages in the Earth System . Berlin : Springer .
Fu R Li W . 2004 . The influence of the land surface on the transition from dry to wet season in Amazonia . Theoretical and Applied Climatology 78 : 97 – 110 .
Gianni A Saravanan R Chang P . 2003 . Oceanic forcing of Sahel rainfall in interannual to interdecedal timescales . Science 302 : 1027 – 1030 .
Givnish TJ . 2002 . Adaptive significance of evergreen vs. deciduous leaves: Solving the triple paradox . Silva Fennica 36 : 703 – 743 .
Goldstein G Andrade JL Meinzer FC Holbrook NM Cavelier J Jackson P Celis A . 1998 . Stem water storage and diurnal patterns of water use in tropical forest canopy trees . Plant, Cell and Environment 21 : 397 – 406 .
Gordon LJ Steffen W Jonsson BF Folke C Falkenmark M Johannessen A . 2005 . Human modification of global water vapor flows from the land surface . Proceedings of the National Academy of Sciences 102 : 7612 – 7617 .
[IPCC] Intergovernmental Panel on Climate Change . 2007 . Climate Change 2007: The Physical Science Basis . Cambridge (United Kingdom) : Cambridge University Press . ( 18 February 2009 ; www.ipcc.ch/ipccreports/ar4-wg1.htm )
Juarez RIN Hodnett MG Fu R Goulden ML von Randow C . 2007 . Control of dry season evapotranspiration over the Amazonian forest as inferred from observations at a southern Amazon forest site . Journal of Climate 20 : 2827 – 2839 .
Koch PL Barnosky AD . 2006 . Late quaternary extinctions: State of the debate . Annual Review of Ecology Evolution and Systematics 37 : 215 – 250 .
Laurance WF . 2005 . Forest-climate interaction in fragmented tropical landscapes . Pages 31 – 38 in Malhi Y Phillips O , eds. Tropical Forests and Global Atmospheric Change . Oxford (United Kingdom) : Oxford University Press .
Lee J E Oliveira RS Dawson TE Fung I . 2005 . Root functioning modifies seasonal climate . Proceedings of the National Academy of Sciences 102 : 17576 – 17581 .
Lenton TM van Oijen M . 2002 . Gaia as a complex adaptive system . Philosophical Transactions of the Royal Society of London B 357 : 683 – 695 .
Lobell DB Burke MB Tebaldi C Mastrandrea MD Falcon WP Naylor RL . 2008 . Prioritizing climate change adaptation needs for food security in 2030 . Science 319 : 607 – 610 .
Loescher HW Gholz HL Jacobs JM Oberbauer SF . 2005 . Energy dynamics and modeled evapotranspiration from a wet tropical forest in Costa Rica . Journal of Hydrology 315 : 274 – 294 .
Makarieva AM Gorshkov VG . 2007 . Biotic pump of atmospheric moisture as driver of the hydrological cycle on land . Hydrology and Earth System Sciences 11 : 1013 – 1033 .
Makarieva AM Gorshkov VG Li BL . 2006 . Conservation of water cycle on land via restoration of natural closed-canopy forests: Implications for regional landscape planning . Ecological Research 21 : 897 – 906 .
Malhi Y Wright J . 2005 . Late twentieth-century patterns and trends in the climate of tropical forest regions . Pages 3 – 16 in Malhi Y Phillips O , eds. Tropical Forests and Global Atmospheric Change . Oxford (United Kingdom) : Oxford University Press .
Marengo JA . 2005 . Characteristics and spatio-temporal variability of the Amazon River Basin Water Budget . Climate Dynamics 24 : 11 – 22 .
Meher-Homji VM . 1980 . Repercussions of deforestation on precipitation in western Karnataka, India . Archiv für Meterologie, Geophysik und Bioklimatologie 28B : 385 – 400 .
Mohamed YA van den Hurk B Savenije HHG Bastiaanssen WGM . 2005 . Hydroclimatology of the Nile: Results from a regional climate model . Hydrology and Earth System Sciences 9 : 263 – 278 .
Morley RJ . 2000 . Origin and Evolution of Tropical Rain Forests . Chichester (United Kingdom) : Wiley .
Myneni RB , et al. . 2007 . Large seasonal swings in leaf area of Amazon rainforests . Proceedings of the National Academy of Sciences 104 : 4820 – 4823 .
Nepstad DC de Carvalho CR Davidson EA Jipp PH Lefebvre PA Negreiros GH da Silva ED Stone TA Trumbore SE Vieira S . 1994 . The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures . Nature 372 : 666 – 669 .
Nesbitt SW Zipser EJ . 2003 . The diurnal cycle of rainfall and convective intensity according to three years of TRMM measurements . Journal of Climate 16 : 1456 – 1475 .
Olchev A Ibrom A Priess J Erasmim S Leemhuis C Twele A Radler K Kreilein H Panferov O Gravenhorst G . 2008 . Effects of land-use changes on evapotranspiration of tropical rain forest margin area in Central Sulawesi (Indonesia): Modelling study with a regional SVAT mode . Ecological Modelling 212 : 131 – 137 .
Pons TL Welschen RAM . 2004 . Midday depression of net photosynthesis in the tropical rainforest tree Eperua grandiflora : Contributions of stomatal and internal conductances, respiration and Rubisco functioning . Tree Physiology 23 : 937 – 947 .
Savenije HHG . 1995 . New definitions for moisture recycling and the relationship with land-use changes in the Sahel . Journal of Hydrology 167 : 57 – 78 .
Savenije HHG . 1996 . The runoff coefficient as the key to moisture recycling . Journal of Hydrology 176 : 219 – 225 .
Savenije HHG . 2004 . The importance of interception and why we should delete the term evapotranspiration from our vocabulary . Hydrological Processes 18 : 1507 – 1511 .
Schnitzer SA . 2005 . A mechanistic explanation for global patterns of liana abundance and distribution . American Naturalist 166 : 262 – 276 .
Sheil D . 2003 . Growth assessment in tropical trees: Large daily diameter fluctuations and their concealment by dendrometer bands . Canadian Journal of Forest Research 33 : 2027 – 2035 .
van der Molen MK Dolman AJ Waterloo MJ Bruijnzeel LA . 2006 . Climate is affected more by maritime than by continental land use change: A multiple scale analysis . Global and Planetary Change 54 : 128 – 149 .
Wang J Chagnon FJF Williams ER Betts AK Renno NO Machado LTT Bisht G Knox R Bras RL . 2009 . Impact of deforestation in the Amazon basin on cloud climatology . Proceedings of the National Academy of Sciences Online Early (published online before print 23 February 2009). doi:10. 1073/pnas.0810156106
Webb TJ Woodward FI Hannah L Gaston KJ . 2005 . Forest cover-rainfall relationships in a biodiversity hotspot: The Atlantic Forest of Brazil . Ecological Applications 15 : 1968 – 1983 .
Zhang H Henderson-Sellers A McGuffie K . 1996 . Impacts of tropical deforestation, I: Process analysis of local climatic change . Journal of Climate 9 : 1497 – 1517 .
Zhou JY Lau KM . 1998 . Does a monsoon climate exist over South America? Journal of Climate 11 : 1020 – 1040 .
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In 2008, to call attention to the issue of deforestation, Harrison Ford, star of the "Indiana Jones" movies, had his chest waxed on camera. "Every bit of rain forest that gets ripped out over there… really hurts us over here," he told viewers as hair was yanked from his pecs [source: AP ].
Ford's public service announcement was in support of an environmental organization called Conservation International, which seeks to prevent deforestation. So, what is deforestation , and why would it motivate a movie star to sacrifice chest hair?
Effects of deforestation, how to protect forests.
Deforestation is the removal or destruction of large areas of forest or rainforest .
Deforestation happens for many reasons, such as logging, agriculture, natural disasters, urbanization and mining.There are several ways to clear forest — burning and clear-cutting the land are two of the more common methods.
Although deforestation occurs worldwide, it's a particularly critical issue in the Amazon rainforests of Brazil. There, the tropical forests, and the species of plants and animals within them, are disappearing at an alarming rate.
The effects of deforestation are long lasting and devastating. Entire species of insects and animals have disappeared because of the destruction of their habitats. Deforestation can cause catastrophic flooding as well. And scientists see that deforestation has a significant effect on climate change, or global warming.
[sources: FAO and Conservation International ]
For the most part, human activity is to blame for deforestation, though natural disasters do play a role. So let's take a look at how and why humans deforest areas.
Logging, or cutting down trees in a forest to harvest timber for wood, products or fuel, is a primary driver of deforestation. Logging affects the environment in several ways. Since trucks and large equipment need to get into the forest in order to access trees and transport timber, loggers must clear large areas for roadways. Most countries regulate logging, but illegal logging remains a problem.
Selective logging — where only the most valuable trees are felled — doesn't help matters, as one falling tree can bring down dozens of surrounding trees and thin the forest's protective canopy [source: Butler ].
The forest canopy is important to the forest's ecosystem because it houses and protects plant, animal and insect populations. It also protects the forest floor, which slows down soil erosion.
Agriculture also drives deforestation. Farmers clear the land for crops or for cattle and often will clear acres of land using slash and burn techniques — cutting down trees and then burning them.
Migratory farmers clear a forest area and use it until the soil becomes too degraded for crops. Then they move on and clear a new patch of forest. The abandoned land, if left untouched, will eventually reforest, but it will take many, many years to return to its original state.
Hydroelectric dams are quite controversial because while they bring electricity to communities, they also contribute to deforestation. Damming opponents believe that the building of such structures not only has a negative environmental impact, but it also opens up the area to loggers and more roads [source: Colitt ].
To build a hydroelectric dam , acres of land must be flooded, which causes decomposition and release of greenhouse gases. Local people can also be displaced by dam projects, causing further deforestation when these people resettle elsewhere.
Fires , both accidental and intended, destroy acres of forest very quickly. Areas affected by logging are more susceptible to fires due to the number of dried, dead trees.
Milder winters and extended warm seasons due to global warming also fuel fires. For example, certain species of beetle that usually die off each winter are now able to survive and continue feeding on trees. This feeding causes the trees to die and dry out, making them into kindling [source: Bentz & Klepzig ].
Mining also results in deforestation. Digging a coal, diamond or gold mine requires the removal of all forest cover, not just for the mines but also for trucks and equipment. Between 2000 and 2019, mining destroyed 1260 square miles (3,264 square kilometers) of forest [source: Giljum et al. ].
Palm oil is found in many packaged foods and beauty products. But palm oil is another cause of deforestation. Demand for palm oil has led growers to clear tropical forests and replace them with a monoculture of palm oil plantations [source: WWF ].
As cities grow larger to accommodate more people, trees are cut down to make more room for houses and roads. This urban sprawl deforestation is occurring worldwide, now that 55 percent of the human population lives in cities [source: UN ].
As miners needed to go deeper and deeper to retrieve coal, the inefficient steam engine needed to become more efficient. Soon it evolved into the modern steam engine and was the foundation of the Industrial Revolution .
Scientists are finding more and more links between deforestation and global warming . The carbon footprint created by four years of deforestation is equal to the projected carbon footprint of every single air flight in the history of aviation up to the year 2025 [source: Kristof ].
Let's break that down into simple logic: Trees absorb carbon dioxide. So, fewer trees means more carbon dioxide is loose in the air. More carbon dioxide means an increased greenhouse effect , which leads to global warming.
Reduced biodiversity is another deforestation concern. Tropical rainforests , arguably the biggest victims of deforestation, cover only about 6 percent of the Earth's land surface [source: WWF ].
However, within this 6 percent live almost half of all plant and animal species on Earth . Some of these species only live in small specific areas, which makes them especially vulnerable to extinction.
As the landscape changes, some plants and animals are simply unable to survive. Species from the tiniest flower to large orangutans are becoming endangered or even extinct. Biologists believe that the key to curing many diseases resides within the biology of these rare plants and animals, and preservation is crucial [source: Lindsey ].
Soil erosion, while a natural process, accelerates with deforestation. Trees and plants act as a natural barrier to slow water as it runs off the land. Roots bind the soil and prevent it from washing away.
The absence of vegetation causes the topsoil to erode more quickly. It's difficult for plants to grow in the less nutritious soil that remains.
Because trees release water vapor into the atmosphere, fewer trees means less rain, which disrupts the water table (or groundwater level). A lowered water table can be devastating for farmers who can't keep crops alive in such dry soil [source: USA Today ].
On the other hand, deforestation can also cause flooding . Coastal vegetation lessens the impact of waves and winds associated with a storm surge. Without this vegetation, coastal villages are susceptible to damaging floods.
The 2008 cyclone in Myanmar proved this fact to catastrophic effect. Scientists believe that the removal of coastal mangrove forests over the past decade caused the cyclone to hit with much more force [source: FAO ].
Deforestation also affects Indigenous people, both physically and culturally. Because many Indigenous groups actually have no legal rights to the land on which they live, governments that want to use the forest for profit can actually "evict" them. As these populations leave the rainforest, they also leave their culture behind [source: Butler ].
The most common theory is deforestation. The inhabitants of Easter Island depended on the giant palms that covered the island. They cut down trees for agricultural purposes, fuel and structures.
Eventually, the trees just ran out. Once the natural resources were gone, so were the people. When Dutch settlers arrived around 1700, they found a barren landscape.
The good news is that efforts to curb deforestation are working. The rate of global deforestation has slowed from 7.8 million hectares per year in 1990–2000 to 4.7 million hectares per year in 2010–2020 [source: FAO ]. However, there's a lot more work to be done.
Here are a few of the organizations working to combat deforestation:
Can we really save the forests? Once the trees are gone, is it possible to restore the land? Most deforested areas, if left alone, will eventually regenerate to fertile landscape. We can certainly plant more trees — a process called reforestation.
In the meantime, new movements in forest protection have sprung up over the years. They include:
[source: Forests.org ]
A little known fact: Bats pollinate, just like bees or butterflies. They eat fruit or nectar, which makes them excellent vehicles for dispersing seeds and pollinating flowers over a wide area. By building artificial bat roosts in deforested areas, researchers hope bats will disperse seeds to reforest the area. A study of these roosts in Latin America showed the dispersal of 60 different types of seeds [source: Science Daily ].
What is deforestation, why is deforestation a problem, what are the five main causes of deforestation, how can we stop deforestation, is there any permanent solution for deforestation, lots more information, related howstuffworks articles.
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May 30, 2020
Controversial new archaeological research casts doubt on a classic theory of this famous island's societal collapse
By Tom Garlinghouse & Sapiens
Daniel Frauchiger Getty Images
Easter Island’s colossal statues loom large—both literally and figuratively—in the popular imagination. The massive heads and torsos dot the landscape like stone sentinels, standing guard over the isle’s treeless, grassy expanse.
The statues have inspired widespread speculation, awe, and wonder for centuries. But the island, called Rapa Nui by its Indigenous people, has also captured the world’s imagination for an entirely different reason.
Rapa Nui is often seen as a cautionary example of societal collapse. In this story, made popular by geographer Jared Diamond’s bestselling book Collapse , the Indigenous people of the island, the Rapanui, so destroyed their environment that, by around 1600, their society fell into a downward spiral of warfare, cannibalism, and population decline. These catastrophes, the collapse narrative explains, resulted in the destruction of the social and political structures that were in place during precolonial times, though the people of Rapa Nui survive and persist on the island to the present day.
If you're enjoying this article, consider supporting our award-winning journalism by subscribing . By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.
In recent years, researchers working on the island have questioned this long-accepted story . For example, anthropologist Terry Hunt and archaeologist Carl Lipo, who have studied the island’s archaeology and cultural history for many years, have suggested an alternative hypothesis that the Rapanui did not succumb to a downward spiral of self-destruction but instead practiced resiliency, cooperation, and perhaps even a degree of environmental stewardship.
Now new evidence from Hunt, Lipo, and their colleagues, published in the Journal of Archaeological Science , lends credence to their ideas. This evidence suggests that the people of the island continued to thrive, as indicated by the continued construction of the stone platforms, called ahu , on which the iconic statues stand, even after the 1600s.
“Our research shows that statue platform construction and use did not end prior to European arrival in 1722,” says Robert DiNapoli, a doctoral student in anthropology at the University of Oregon, who led the study.
This finding, drawing on new statistical methods and excavation work, suggests that the Rapanui were not destitute when the first Europeans arrived. It’s therefore possible that it was the newcomers from Europe who contributed to the island’s societal collapse in the years to come.
The new work is controversial, and not everyone is convinced. But if DiNapoli and his team are correct, the popular story of Rapa Nui’s decline, as described by Diamond, needs to be rethought and its heroes and villains reconfigured. Instead of the Rapanui hastening their own destruction prior to European contact, it is possible that the people of the island may have been the victims of European exploration and exploitation.
Rapa Nui is one of the most remote islands in the world. A tiny speck in the eastern Pacific, it sits more than 2,000 miles west of South America and is about 1,200 miles from its nearest island neighbor, Pitcairn Island.
Archaeologists have documented at least 360 ahu, most of which cluster along the island’s shoreline. They vary in configuration, though most are typically rectangular in shape and are made of basaltic stones neatly fitted together. In addition to their use as statue platforms, the ahu functioned as shrines and places of burial.
DiNapoli and his colleagues used existing radiocarbon dates from previous excavations at 11 different ahu sites. They employed what is called Bayesian analyses, which allow scientists to model the probability of specific events, to build a more precise timeline of construction activities at each site.
The new research indicates that ahu construction began soon after the first Polynesian settlers arrived on the island and continued even after European contact in 1722. This timeline argues against the hypothesized societal collapse occurring around 1600.
The downturn of the islanders, DiNapoli and his colleagues claim, began only after Europeans ushered in a period characterized by disease, murder, slave raiding, and other conflicts.
Not all Rapa Nui specialists agree with DiNapoli and his colleagues’ methods or conclusions. Jo Anne Van Tilburg, an archaeologist at the University of California, Los Angeles, is skeptical that all the radiocarbon dates used by the team reflect specifically ahu-related building events.
Van Tilburg also argues that Diamond’s environmental destruction argument remains a viable hypothesis. “The collapse narrative as these authors describe it is a straw man they have set up that does not accurately reflect the actual hypothesis,” she says.
If Europeans were to blame for the decline of Rapanui society, it would be similar to what happened to Indigenous peoples elsewhere.
In short, Van Tilburg believes the new work is missing some of the nuances of Diamond’s original theory. Diamond never described the collapse as a one-time event, Van Tilburg explains, but rather as a series of events that ultimately resulted in destructive societal changes that were hastened by European contact.
Diamond’s hypothesis is based on a mix of oral tradition, evidence of island deforestation, and the work of previous researchers, such as the Norwegian explorer and ethnologist Thor Heyerdahl. (Heyerdahl gained fame in 1947 for sailing a balsa raft, the Kon-Tiki , to test the theory that South Americans may have colonized Polynesia.)
Early 20th-century oral historians working on Rapa Nui theorized that an internecine clash had occurred between islanders. Heyerdahl later popularized his belief that this warfare, combined with deforestation, resulted in the collapse of the island’s social hierarchies and many traditions, such as the building of stone platforms and statues.
The fate of Rapa Nui has been heatedly debated over the last several years with the development of new theories and innovative techniques, such as Bayesian methods. For many archaeologists, the pre-contact collapse theory is ripe for questioning.
Speaking of the research conducted by DiNapoli’s team, for example, Seth Quintus, an anthropologist at the University of Hawaiʻi, Mānoa, who was not involved in the study, says, “Their work adds to the growing body of evidence that has accumulated over the last 10 years that the previous narratives of collapse on Easter Island are not correct—and need to be rethought.”
If Europeans were to blame for the decline of Rapanui society, that explanation is similar to what happened to other Indigenous peoples elsewhere throughout the world, DiNapoli notes. From that perspective, he says, the popular story of environmental destruction has obscured the islanders’ successes.
“The degree to which their cultural heritage was passed on—and is still present today through language, arts, and cultural practices—is quite notable and impressive,” DiNapoli says. “This degree of resilience has been overlooked due to the collapse narrative and deserves recognition.”
This work first appeared on SAPIENS under a CC BY-ND 4.0 license . Read the original here .
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This paper aimed at evaluating the validity of the deforestation-induced Environmental Kuznets Curve hypothesis controlling for the democracy between 1971 and 2018 in Bangladesh. The cointegration results provide statistical evidence of long-run associations between economic growth, deforestation propensities and the quality of democracy. The elasticity estimates certify the validity of the EKC hypothesis for all the three indicators of deforestation used in this paper: forest area coverage, deforestation rate and net forest depletion rate. Moreover, controlling for democracy lowers the threshold level of growth beyond which the marginal impact of growth results in environmental betterment by reducing the deforestation propensities in Bangladesh. Moreover, democracy and economic growth are also seen to exert a combined impact on the growth-deforestation nexus. The estimated growth thresholds are above the current real GDP level of Bangladesh which reasons the nation’s deforestation woes. Finally, the causality results also affirm causal associations between economic growth, deforestation and the quality of democracy. Thus, these findings impose key policy implications keeping into cognizance the sustainable economic and environmental development goals of Bangladesh.
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The link between trade openness and deforestation for environmental quality in nigeria.
For more information on the EKC hypothesis see Grossman and Krueger ( 2011 ).
For more information regarding renewable energy transition see Murshed ( 2019 ) and Murshed and Tanha ( 2020 ).
For more information on the CMR approach see Clemente, Monantes and Reyes (1998).
For more information on CC regression see Han ( 1996 ).
Ahiduzzaman, M., & Islam, A. S. (2011). Greenhouse gas emission and renewable energy sources for sustainable development in Bangladesh. Renewable and Sustainable Energy Reviews, 15 (9), 4659–4666.
Google Scholar
Ahmed, A., Bekiros, S., Rosklint-Lindvall, E., Uddin, G. S., & Salvi, A. (2020). The influence of energy consumption and democratic institutions on output and CO 2 emissions in Bangladesh: a time-frequency approach. Energy Systems, 11 (1), 195–212.
Ahmed, K., Shahbaz, M., Qasim, A., & Long, W. (2015). The linkages between deforestation, energy and growth for environmental degradation in Pakistan. Ecological Indicators, 49 , 95–103.
Amarawickrama, H. A., & Hunt, L. C. (2008). Electricity demand for Sri Lanka: a time series analysis. Energy, 33 (5), 724–739.
Banerjee, P. K., & Rahman, M. (2012). Some determinants of carbon dioxide emissions in Bangladesh. International Journal of Green Economics, 6 (2), 205–215.
Barbier, E. B. (2004). Explaining agricultural land expansion and deforestation in developing countries. American Journal of Agricultural Economics, 86 (5), 1347–1353.
Barbier, E. B., & Burgess, J. C. (2001). The economics of tropical deforestation. Journal of Economic Surveys, 15 (3), 413–433.
Benavides, M., Ovalle, K., Torres, C., & Vinces, T. (2017). Economic growth, renewable energy and methane emissions: is there an environmental Kuznets Curve in Austria? International Journal of Energy Economics and Policy, 7 (1), 259–267.
Bhattarai, M., & Hammig, M. (2001). Institutions and the environmental Kuznets curve for deforestation: a cross-country analysis for Latin America. Africa and Asia. World Development, 29 (6), 995–1010.
Bimonte, S., & Stabile, A. (2017). Land consumption and income in Italy: a case of inverted EKC. Ecological Economics, 131 , 36–43.
Bonan, G. B. (2008). Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science, 320 (5882), 1444–1449.
Buitenzorgy, M., & Mol, A. P. (2011). Does democracy lead to a better environment? Deforestation and the democratic transition peak. Environmental and Resource Economics, 48 (1), 59–70.
Busch, J., & Ferretti-Gallon, K. (2017). What drives deforestation and what stops it? A meta-analysis. Review of Environmental Economics and Policy, 11 (1), 3–23.
Chang, Y., & Cho, T. (2005). Democracy and environment: The effect of democratization on environment outcomes in Asia. In Annual meeting of The Midwest Political Science Association, Palmer House Hilton, Chicago, Illinois. Available at http://www.allacademic.com//meta/pmlaaparesearchcitation/0/8/5/3/7/pages85373/p85373-1.php . Accessed 5 Jan 2010.
Chiu, Y. B. (2012). Deforestation and the environmental Kuznets curve in developing countries: A panel smooth transition regression approach. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, 60 (2), 177–194.
Cho, C. H., Chu, Y. P., & Yang, H. Y. (2014). An environment Kuznets curve for GHG emissions: a panel cointegration analysis. Energy Sources, Part B: Economics, Planning, and Policy, 9 (2), 120–129.
Choumert, J., Motel, P. C., & Dakpo, H. K. (2013). Is the Environmental Kuznets Curve for deforestation a threatened theory? A meta-analysis of the literature. Ecological Economics, 90 , 19–28.
Clemente, J., Montañés, A., & Reyes, M. (1998). Testing for a unit root in variables with a double change in the mean. Economics Letters, 59 (2), 175–182.
Coppedge, M., Gerring, J., Knutsen, C. H., Lindberg, S. I., Skaaning, S., Teorell, J., et al. (2018). “V-Dem [Country-Year/Country-Date] Dataset v8” Varieties of Democracy (V-Dem) Project.
Deacon, R., & Mueller, B. (2004). Political economy and natural resource use, Department of Economics, UCSB. Departmental Working Papers 01-04.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74 (366a), 427–431.
Dogan, E., & Turkekul, B. (2016). CO 2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the EKC hypothesis for the USA. Environmental Science and Pollution Research, 23 (2), 1203–1213.
Ehrhardt-Martinez, K., Crenshaw, E. M., & Jenkins, J. C. (2002). Deforestation and the environmental Kuznets curve: A cross-national investigation of intervening mechanisms. Social Science Quarterly, 83 (1), 226–243.
Emas, R. (2015). The concept of sustainable development: definition and defining principles. Brief for GSDR, 2015. Available at: https://www.academia.edu/download/43652555/5839GSDR_2015_SD_concept_definiton_rev.pdf
Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica, 55 (2), 251–276.
Esposito, P., Patriarca, F., Perini, L., & Salvati, L. (2016). Land degradation, economic growth and structural change: evidences from Italy. Environment, development and sustainability, 18 (2), 431–448.
Ewel, K., Twilley, R., & Ong, J. I. N. (1998). Different kinds of mangrove forests provide different goods and services. Global Ecology & Biogeography Letters, 7 (1), 83–94.
Gill, A. R., Hassan, S., & Viswanathan, K. K. (2019). Is democracy enough to get early turn of the environmental Kuznets curve in ASEAN countries?. Energy and Environment,30(8), 1491-1505 0958305X19851349.
Gokmenoglu, K. K., Olasehinde-Williams, G. O., & Taspinar, N. (2019). Testing the environmental Kuznets curve hypothesis: the role of deforestation. In Energy and Environmental Strategies in the Era of Globalization (pp. 61–83). Springer, Cham.
Gorus, M. S., & Aslan, M. (2019). Impacts of economic indicators on environmental degradation: evidence from MENA countries. Renewable and Sustainable Energy Reviews, 103 , 259–268.
Gossman, P. (2017). Government corruption exacerbating Bangladesh’s environmental catastrophes. Human Rights Watch. Available at: https://www.hrw.org/news/2017/07/11/government-corruption-exacerbating-bangladeshs-environmental-catastrophes
Graven, H. D. (2015). Impact of fossil fuel emissions on atmospheric radiocarbon and various applications of radiocarbon over this century. Proceedings of the National Academy of Sciences, 112 (31), 9542–9545.
Gregory, A. W., & Hansen, B. E. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of econometrics, 70 (1), 99–126.
Grossman, G. M., & Krueger, A. B. (2011). Environmental impacts of a North American free trade agreement. Working Paper No. w3914. National Bureau of Economic Research Available at: https://www.nber.org/papers/w3914.pdf .
Hacker, R. S., & Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application. Applied Economics, 38 (13), 1489–1500.
Hacker, S., & Hatemi-J, A. (2012). A bootstrap test for causality with endogenous lag length choice: theory and application in finance. Journal of Economic Studies, 39 (2), 144–160.
Han, H. L. (1996). Small sample properties of canonical cointegrating regressions. Empirical Economics, 21 (2), 235–253.
Hao, Y., Xu, Y., Zhang, J., Hu, X., Huang, J., Chang, C. P., et al. (2019). Relationship between forest resources and economic growth: Empirical evidence from China. Journal of cleaner production, 214 , 848–859.
Hasanov, F. J., Mikayilov, J. I., Mukhtarov, S., & Suleymanov, E. (2019). Does CO 2 emissions–economic growth relationship reveal EKC in developing countries? Evidence from Kazakhstan. Environmental Science and Pollution Research, 26 (29), 30229–30241.
Iftekhar, M. S., & Hoque, A. F. (2005). Causes of forest encroachment: An analysis of Bangladesh. GeoJournal , 62 (1–2), 95–106.
Ike, G. N., Usman, O., & Sarkodie, S. A. (2020). Fiscal policy and CO2 emissions from heterogeneous fuel sources in Thailand: Evidence from multiple structural breaks cointegration test. Science of the Total Environment, 702 , 134711.
Islam, K., & Sato, N. (2012). Deforestation, land conversion and illegal logging in Bangladesh: the case of the Sal (Shorea robusta) forests. iForest-Biogeosciences and Forestry , 5 (3), 171.
Islam, F., Shahbaz, M., & Butt, M. S. (2013). Is there an environmental Kuznets curve for Bangladesh? Evidence from ARDL bounds testing approach. The Bangladesh Development Studies, 36 (4), 1–23.
Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica Journal of the Econometric Society, 59 (6), 1551–1580.
Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52 (2), 169–210.
Joshi, P., & Beck, K. (2016). Environmental Kuznets curve for deforestation: evidence using GMM estimation for OECD and non-OECD regions. iForest-Biogeosciences and Forestry, 10 (1), 196.
Kant, S., Nautiyal, J. C., & Berry, R. A. (1996). Forests and economic welfare. Journal of Economic Studies, 23 (2), 31–43.
Kashem, M. A., & Rahman, M. M. (2019). CO 2 Emissions and Development Indicators: a Causality Analysis for Bangladesh. Environmental Processes, 6 (2), 433–455.
Khan, M. T. I., Ali, Q., & Ashfaq, M. (2018). The nexus between greenhouse gas emission, electricity production, renewable energy and agriculture in Pakistan. Renewable Energy, 118 , 437–451.
Kumar, P., & Aggarwal, S. C. (2003). The environmental Kuznets curve for changing land use: Empirical evidence from major states of India. International journal of sustainable development. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=991080 .
Kuznets, S. (1955). Economic growth and income inequality. The American economic review, 45 (1), 1–28.
Lantz, V. (2002). Is there an Environmental Kuznets Curve for clearcutting in Canadian forests? Journal of Forest Economics, 8 (3), 199–212.
Lee, C. C., Chiu, Y. B., & Sun, C. H. (2009). Deforestation, environmental Kuznets curve, and threshold effects: International evidence. In Singapore Economic Review Conference. Available at: https://pdfs.semanticscholar.org/75b8/267456dff9b8619ad2ce1220915020a58595.pdf .
Lee, C. C., Chiu, Y. B., & Sun, C. H. (2010). The environmental Kuznets curve hypothesis for water pollution: Do regions matter? Energy Policy, 38 (1), 12–23.
Maji, I. K. (2017). The link between trade openness and deforestation for environmental quality in Nigeria. GeoJournal, 82 (1), 131–138.
Maki, D. (2012). Tests for cointegration allowing for an unknown number of breaks. Economic Modelling, 29 (5), 2011–2015.
Mason, C. L., & Lippke, B. R. (2007). Jobs, revenues, and taxes from timber harvest: An examination of the forest industry contribution to the Washington State economy. Working Paper. College of Forest Resources, University of Washington, Seattle.
McCarthy, S., & Tacconi, L. (2011). The political economy of tropical deforestation: assessing models and motives. Environmental Politics, 20 (1), 115–132.
Miah, M. D., Masum, M. F. H., Koike, M., & Akther, S. (2011). A review of the environmental Kuznets curve hypothesis for deforestation policy in Bangladesh. iForest-Biogeosciences and Forestry, 4 (1), 16.
Murshed, M. (2018). Does improvement in trade openness facilitate renewable energy transition? Evidence from selected South Asian economies. South Asia Economic Journal, 19 (2), 151–170. https://doi.org/10.1177/1391561418794691 .
Article Google Scholar
Murshed, M. (2019). Are Trade Liberalization policies aligned with Renewable Energy Transition in low and middle income countries? An Instrumental Variable approach. Renewable Energy, 151 , 1111–1123. https://doi.org/10.1016/j.renene.2019.11.106 .
Murshed, M. (2020). A empirical analysis of the non-linear impacts of ICT-Trade Openness on Renewable Energy Transition, Energy Efficiency, Clean cooking fuel access and Environmental Sustainability in South Asia. Environmental Science and Pollution Research . https://doi.org/10.1007/s11356-020-09497-3 .
Murshed, M., & Tanha, M. M. (2020). Oil price shocks and renewable energy transition: Empirical evidence from net oil-importing South Asian economies. Energy, Ecology & Environment . https://doi.org/10.1007/s40974-020-00168-0 .
Naidoo, R. (2004). Economic growth and liquidation of natural capital: the case of forest clearance. Land Economics, 80 (2), 194–208.
Naito, T., & Traesupap, S. (2014). The relationship between mangrove deforestation and economic development in Thailand. In Mangrove Ecosystems of Asia (pp. 273–294). Springer, New York.
Odum, H. T. (1996). Environmental accounting: emergy and environmental decision making (p. 370). New York: Wiley.
Ogundari, K., Ademuwagun, A. A., & Ajao, O. A. (2017). Revisiting environmental Kuznets curve in Sub-Sahara Africa: evidence from deforestation and all GHG emissions from agriculture. International Journal of Social Economics, 44 (2), 222–231.
Park, J. Y. (1992). Canonical cointegrating regressions. Econometrica Journal of the Econometric Society, 60 (2), 119–143.
Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica Journal of the Econometric Society, 57 (6), 1361–1401.
Perron, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics, 8 (2), 153–162.
Perron, P., & Vogelsang, T. J. (1992a). Nonstationarity and level shifts with an application to purchasing power parity. Journal of Business and Economic Statistics, 10 (3), 301–320.
Perron, P., & Vogelsang, T. J. (1992b). Testing for a unit root in a time series with a changing mean: corrections and extensions. Journal of Business and Economic Statistics, 10 (4), 467–470.
Phillips, P. C., & Hansen, B. E. (1990). Statistical inference in instrumental variables regression with I (1) processes. The Review of Economic Studies, 57 (1), 99–125.
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75 (2), 335–346.
Pouliotte, J., Smit, B., & Westerhoff, L. (2009). Adaptation and development: Livelihoods and climate change in Subarnabad. Bangladesh. Climate and Development , 1 (1), 31–46.
Psaltopoulos, D., & Thomson, K. J. (1993). Input-output evaluation of rural development: a forestry-centred application. Journal of Rural Studies, 9 (4), 351–358.
Rabbi, F., Akbar, D., & Kabir, S. Z. (2015). Environment Kuznets curve for carbon emissions: A cointegration analysis for Bangladesh. International Journal of Energy Economics and Policy, 5 (1), 45–53.
Rahman, M. M., & Kashem, M. A. (2017). Carbon emissions, energy consumption and industrial growth in Bangladesh: Empirical evidence from ARDL cointegration and Granger causality analysis. Energy Policy, 110 , 600–608.
Rahman, M. M., Rahman, M. M., & Islam, K. S. (2010). The causes of deterioration of Sundarban mangrove forest ecosystem of Bangladesh: conservation and sustainable management issues. Aquaculture, Aquarium, Conservation & Legislation, 3 (2), 77–90.
Reza, A. A., & Hasan, M. K. (2019). Forest biodiversity and deforestation in Bangladesh: the latest update. In Deforestation Around the World. IntechOpen. Available at: https://www.intechopen.com/online-first/forest-biodiversity-and-deforestation-in-bangladesh-the-latest-update
Shafik, N., & Bandyopadhyay, S. (1992). Economic growth and environmental quality: time-series and cross-country evidence (Vol. 904). World Bank Publications, Washington, D.C.
Shahbaz, M., Uddin, G. S., Rehman, I. U., & Imran, K. (2014). Industrialization, electricity consumption and CO2 emissions in Bangladesh. Renewable and Sustainable Energy Reviews, 31 , 575–586.
Shandra, J. M. (2007). The world polity and deforestation: a quantitative, cross-national analysis. International Journal of Comparative Sociology, 48 (1), 5–27.
Sinha, A., & Sengupta, T. (2019). Impact of energy mix on nitrous oxide emissions: an environmental Kuznets curve approach for APEC countries. Environmental Science and Pollution Research, 26 (3), 2613–2622.
Sulemana, I., James, H. S., & Rikoon, J. S. (2017). Environmental Kuznets Curves for air pollution in African and developed countries: exploring turning point incomes and the role of democracy. Journal of Environmental Economics and Policy, 6 (2), 134–152.
Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66 (1–2), 225–250.
Tsiantikoudis, S., Zafeiriou, E., Kyriakopoulos, G., & Arabatzis, G. (2019). Revising the environmental Kuznets Curve for deforestation: an empirical study for Bulgaria. Sustainability, 11 (16), 4364.
UNICEF. (2018). The Rohingya Refugee crisis. United Nations International Children’s Education Fund. Available at: https://www.unicef.org/bangladesh/en/rohingya-refugee-crisis-0
Vaona, A. (2012). Granger non-causality tests between (non) renewable energy consumption and output in Italy since 1861: the (ir) relevance of structural breaks. Energy Policy, 45 , 226–236.
Van Khuc, Q., Tran, B. Q., Meyfroidt, P., & Paschke, M. W. (2018). Drivers of deforestation and forest degradation in Vietnam: an exploratory analysis at the national level. Forest policy and economics, 90 , 128–141.
Waluyo, E. A., & Terawaki, T. (2016). Environmental Kuznets curve for deforestation in Indonesia: an ARDL bounds testing approach. Journal of Economic Cooperation & Development, 37 (3), 87–108.
World Bank. (2018). World Development Indicators . Washington DC: World Bank.
Zambrano-Monserrate, M. A., Carvajal-Lara, C., Urgilés-Sanchez, R., & Ruano, M. A. (2018). Deforestation as an indicator of environmental degradation: analysis of five European countries. Ecological Indicators, 90 , 1–8.
Zhang, C., Wang, Y., Song, X., Kubota, J., He, Y., Tojo, J., et al. (2017). An integrated specification for the nexus of water pollution and economic growth in China: panel cointegration, long-run causality and environmental Kuznets curve. Science of the Total Environment, 609 , 319–328.
Zhou, Z., Ye, X., & Ge, X. (2017). The impacts of technical progress on sulfur dioxide Kuznets curve in China: a spatial panel data approach. Sustainability, 9 (4), 674.
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Muntasir Murshed
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Murshed, M. Revisiting the deforestation-induced EKC hypothesis: the role of democracy in Bangladesh. GeoJournal 87 , 53–74 (2022). https://doi.org/10.1007/s10708-020-10234-z
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Published : 13 June 2020
Issue Date : February 2022
DOI : https://doi.org/10.1007/s10708-020-10234-z
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Deforestation is one of the critical issues in our global climate change era. It leads to two important environmental challenges, loss of biodiversity and increasing of greenhouse gas emission ...
Abstract This article updates our previous comprehensive meta-analysis of what drives and stops deforestation (Busch and Ferretti-Gallon 2017). By including six additional years of research, this article more than doubles the evidence base to 320 spatially explicit econometric studies published in peer-reviewed academic journals from 1996 to 2019. We find that deforestation is consistently ...
In this paper we afford a quantitative analysis of the sustainability of current world population growth in relation to the parallel deforestation process adopting a statistical point of view. We ...
The "win-win" hypothesis is based on the assumption that poverty is the root cause of deforestation, and hence higher income leads to more forest cover or less deforestation.
Arild Angelsen • David Kaimowitz This article, which synthesizes the results of more than 140 economic models analyzing the causes of tropical deforestation, raises significant doubts about many conventional hypotheses in the debate about deforestation. More roads, higher agricultural prices, lower wages, and a shortage of off-farm employment generally lead to more deforestation. How ...
The EKC hypothesis has also been applied to the field of deforestation, with Cropper and Griffiths (1994) being one of the first studies in this topic. The EKC hypothesis for deforestation states that, at the beginning of a country's economic expansion, there are high standards of natural forest conservation.
How do deforestation and reforestation affect tropical soils and their ecosystem services? This Review synthesizes the latest research and provides policy recommendations.
This paper makes a novel attempt to test the validity of the environmental Kuznets curve hypothesis in the context of Bangladesh using deforestation propensities as indicators of environmental adversities and controlling for energy consumption, agricultural land coverage and population growth rate. Using annual frequency data from 1972 to 2018, the short- and long-run elasticity estimates from ...
In this research, we seek to establish statistical evidence for the EKC hypothesis as applied to deforestation occurring within the Africa continent from 1990 to 2016. This study attempts to address the following question: is it feasible to reduce deforestation among Africa countries while simultaneously developing an economy?
The study also reported evidence consistent with the hypothesis that agricultural projects in CDD villages facilitated expansion of cropland, which resulted in increased deforestation rates.
deforestation pattern in term s of GDP per capita for Latin America and Africa, but this pattern was rejected for Asia. Similarly, distinguishing be tween OECD and non-OEC D countries for the ...
We contribute to this literature by estimating the aggregated and disaggregated effects of economic activities on deforestation in the Congo Basin, a region that has experienced an increase in deforestation in recent years. We further test for the presence of an Environmental Kuznets Curve hypothesis between deforestation and economic activities.
Deforestation may reduce local and downwind precipitation and runoff through reduced water vapor supply to the atmosphere by moisture recycling and may also influence precipitation through mesoscale circulation and moisture transport (29-32).This precipitation feedback to vegetation changes is found to be scale and region dependent ().While small-scale deforestation and associated spatial ...
Abstract: Deforestation in the tropical developing countries is the critical environmental concern to ecologists and environmentalists. Environmental Kuznets Curve (EKC) hypothesis is critical to understanding the development path of a nation in relevance to its environment.
Significance. Millions of people globally rely on forest-based resources for their livelihoods, particularly in the tropics and subtropics. Deforestation is often hypothesized to diminish forest-dependent communities' resource base and to push them toward more-marginal environments, but such ecological marginalization has rarely been quantified.
The goals intended to halve deforestation by 2020, and stop it by 2030. But assessments have concluded we're actually further from stopping deforestation now than we were six years ago. Despite the challenges, the goals can still be achieved with the right measures. In 2014, the future of forests looked bright.
This study examines the validity of the environmental Kuznets curve (EKC) hypothesis by augmenting the model with renewable energy consumption, fossil fuel energy consumption, urbanization, and deforestation. The ten countries that jointly own two-thirds of the...
Deforestation, clearing or thinning of forests by humans to make the land available for other uses. Deforestation is a major driver of terrestrial habitat loss and habitat fragmentation and contributes to global warming. Learn about historical and modern deforestation and its effects.
Abstract. A new hypothesis suggests that forest cover plays a much greater role in determining rainfall than previously recognized. It explains how forested regions generate large-scale flows in atmospheric water vapor. Under this hypothesis, high rainfall occurs in continental interiors such as the Amazon and Congo river basins only because of ...
Biodiversity. Reduced biodiversity is another deforestation concern. Tropical rainforests, arguably the biggest victims of deforestation, cover only about 6 percent of the Earth's land surface [source: WWF].. However, within this 6 percent live almost half of all plant and animal species on Earth.Some of these species only live in small specific areas, which makes them especially vulnerable to ...
Diamond's hypothesis is based on a mix of oral tradition, evidence of island deforestation, and the work of previous researchers, such as the Norwegian explorer and ethnologist Thor Heyerdahl.
This paper aimed at evaluating the validity of the deforestation-induced Environmental Kuznets Curve hypothesis controlling for the democracy between 1971 and 2018 in Bangladesh. The cointegration results provide statistical evidence of long-run associations between economic growth, deforestation propensities and the quality of democracy. The elasticity estimates certify the validity of the ...
Hypothesis - Deforestation. Deforestation has became a big problem in the United States. Cutting down the. trees takes most of the oxygen away and will make it hard to breathe. The trees. are important because we need them for the oxygen.