hypothesis for deforestation

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• Review Article
• Published: 15 September 2020

Deforestation and reforestation impacts on soils in the tropics

• Edzo Veldkamp   ORCID: orcid.org/0000-0002-8318-8349 1 ,
• Marcus Schmidt   ORCID: orcid.org/0000-0002-5546-5521 1 ,
• Jennifer S. Powers 2 , 3 &
• Marife D. Corre 1  

Nature Reviews Earth & Environment volume  1 ,  pages 590–605 ( 2020 ) Cite this article

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• Biogeochemistry
• Carbon cycle
• Element cycles
• Environmental impact

Soils under natural, tropical forests provide essential ecosystem services that have been shaped by long-term soil–vegetation feedbacks. However, deforestation of tropical forest, with a net rate of 5.5 million hectares annually in 2010–2015, profoundly impacts soil properties and functions. Reforestation is also prominent in the tropics, again altering the state and functioning of the underlying soils. In this Review, we discuss the substantial changes in dynamic soil properties following deforestation and during reforestation. Changes associated with deforestation continue for decades after forest clearing eventually extend to deep subsoils and strongly affect soil functions, including nutrient storage and recycling, carbon storage and greenhouse gas emissions, erosion resistance and water storage, drainage and filtration. Reforestation reverses many of the effects of deforestation, mainly in the topsoil, but such restoration can take decades and the resulting soil properties still deviate from those under natural forests. Improved management of soil organic matter in converted land uses can moderate or reduce the ecologically deleterious effects of deforestation on soils. We emphasize the importance of soil knowledge not only in cross-disciplinary research on deforestation and reforestation but also in developing effective incentives and policies to reduce deforestation.

Deforestation leads to profound changes in dynamic soil properties that degrade most soil functions.

The rate and degree of soil degradation following deforestation are a function of the inherent soil fertility and land-use intensity.

Changes in dynamic soil properties continue for decades following deforestation and eventually extend to deep subsoils.

Reforestation reverses some of the undesirable effects of deforestation on dynamic soil properties; however, the resulting soil conditions and their functions are substantially different from the previous soils under natural forests.

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Koch, A. et al. Soil security: solving the global soil crisis. Glob. Policy 4 , 434–441 (2013).

Google Scholar  

Vogel, H.-J. et al. A systemic approach for modeling soil functions. SOIL 4 , 83–92 (2018).

Corre, M. D., Veldkamp, E., Arnold, J. & Wright, S. J. Impact of elevated N input on soil N cycling and losses in old-growth lowland and montane forests in Panama. Ecology 91 , 1715–1729 (2010).

Cusack, D. F., Markesteijn, L., Condit, R., Lewis, O. T. & Turner, B. L. Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots. Biogeochemistry 137 , 253–266 (2018).

Vitousek, P. M. & Sanford, R. L. Nutrient cycling in moist tropical forest. Annu. Rev. Ecol. Syst. 17 , 137–167 (1986).

Powers, J. S., Corre, M. D., Twine, T. E. & Veldkamp, E. Geographic bias of field observations of soil carbon stocks with tropical land-use changes precludes spatial extrapolation. Proc. Natl Acad. Sci. USA 108 , 6318–6322 (2011).

Don, A., Schumacher, J. & Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks - a meta-analysis. Glob. Change Biol. 17 , 1658–1670 (2011).

Chaves, J. et al. Land management impacts on runoff sources in small Amazon watersheds. Hydrol. Process. 22 , 1766–1775 (2008).

Nepstad, D. C. et al. The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures. Nature 372 , 666–669 (1994).

Elsenbeer, H. Hydrologic flowpaths in tropical rainforest soilscapes-a review. Hydrol. Process. 15 , 1751–1759 (2001).

Markewitz, D., Davidson, E., Moutinho, P. & Nepstad, D. Nutrient loss and redistribution after forest clearing on a highly weathered soil in Amazonia. Ecol. Appl. 14 , 177–199 (2004).

Barnes, A. D. et al. Direct and cascading impacts of tropical land-use change on multi-trophic biodiversity. Nat. Ecol. Evol. 1 , 1511–1519 (2017).

Clark, D. B., Palmer, M. W. & Clark, D. A. Edaphic factors and the landscape-scale distributions of tropical rain forest trees. Ecology 80 , 2662–2675 (1999).

Jones, M. M. et al. Explaining variation in tropical plant community composition: influence of environmental and spatial data quality. Oecologia 155 , 593–604 (2008).

Canadell, J. et al. Maximum rooting depth of vegetation types at the global scale. Oecologia 108 , 583–595 (1996).

Barnes, A. D. et al. Consequences of tropical land use for multitrophic biodiversity and ecosystem functioning. Nat. Commun. 5 , 5351 (2014).

Grass, I. et al. Trade-offs between multifunctionality and profit in tropical smallholder landscapes. Nat. Commun. 11 , 1186 (2020).

Davidson, E. A. et al. Recuperation of nitrogen cycling in Amazonian forests following agricultural abandonment. Nature 447 , 995–998 (2007).

Jobbágy, E. G. & Jackson, R. B. The distribution of soil nutrients with depth: global patterns and the imprint of plants. Biogeochemistry 53 , 51–77 (2001).

Clough, Y. et al. Land-use choices follow profitability at the expense of ecological functions in Indonesian smallholder landscapes. Nat. Commun. 7 , 13137 (2016).

Lewis, S. L., Edwards, D. P. & Galbraith, D. Increasing human dominance of tropical forests. Science 349 , 827–832 (2015).

Roberts, P., Hunt, C., Arroyo-Kalin, M., Evans, D. & Boivin, N. The deep human prehistory of global tropical forests and its relevance for modern conservation. Nat. Plants 3 , 17093 (2017).

Ribeiro Filho, A. A., Adams, C., Manfredini, S., Aguilar, R. & Neves, W. A. Dynamics of soil chemical properties in shifting cultivation systems in the tropics: a meta-analysis. Soil Use Manag. 31 , 474–482 (2015).

Jarosz, L. Defining and explaining tropical deforestation: shifting cultivation and population growth in colonial Madagascar (1896–1940). Econ. Geogr. 69 , 366–379 (1993).

Lambin, E. F. et al. The causes of land-use and land-cover change: moving beyond the myths. Glob. Environ. Change 11 , 261–269 (2001).

Rudel, T. K., Defries, R., Asner, G. P. & Laurance, W. F. Changing drivers of deforestation and new opportunities for conservation. Conserv. Biol. 23 , 1396–1405 (2009).

Keenan, R. J. et al. Dynamics of global forest area: results from the FAO Global Forest Resources Assessment 2015. For. Ecol. Manag. 352 , 9–20 (2015).

Busch, J. et al. Potential for low-cost carbon dioxide removal through tropical reforestation. Nat. Clim. Change 9 , 463–466 (2019).

Morales-Hidalgo, D., Oswalt, S. N. & Somanathan, E. Status and trends in global primary forest, protected areas, and areas designated for conservation of biodiversity from the Global Forest Resources Assessment 2015. For. Ecol. Manag. 352 , 68–77 (2015).

Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530 , 211–214 (2016).

Davidson, E. A., Keller, M., Erickson, H. E., Verchot, L. V. & Veldkamp, E. Testing a conceptual model of soil emissions of nitrous and nitric oxides. BioScience 50 , 667–680 (2000).

Kurniawan, S. et al. Conversion of tropical forests to smallholder rubber and oil palm plantations impacts nutrient leaching losses and nutrient retention efficiency in highly weathered soils. Biogeosciences 15 , 5131–5154 (2018).

Detwiler, R. P. Land use change and the global carbon cycle: the role of tropical soils. Biogeochemistry 2 , 67–93 (1986).

Guo, L. B. & Gifford, R. M. Soil carbon stocks and land use change: a meta analysis. Glob. Change Biol. 8 , 345–360 (2002).

Davidson, E. A. & Ackerman, I. L. Changes in soil carbon inventories following cultivation of previously untilled soils. Biogeochemistry 20 , 161–193 (1993).

Veldkamp, E. Organic carbon turnover in three tropical soils under pasture after deforestation. Soil Sci. Soc. Am. J. 58 , 175–180 (1994).

Nye, P. H. & Greenland, D. J. Changes in the soil after clearing tropical forest. Plant Soil 21 , 101–112 (1964).

van Straaten, O. et al. Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon. Proc. Natl Acad. Sci. USA 112 , 9956–9960 (2015).

Tugel, A. J. et al. Soil change, soil survey, and natural resources decision making. Soil Sci. Soc. Am. J. 69 , 738–747 (2005).

Sanchez, P. A. Properties and Management of Soils in the Tropics 2nd edn (Cambridge Univ. Press, 2019).

van Breemen, N., Mulder, J. & Driscoll, C. T. Acidification and alkalinization of soils. Plant Soil 75 , 283–308 (1983).

Andriesse, J. P. & Schelhaas, R. M. A monitoring study on nutrient cycles in soils used for shifting cultivation under various climatic conditions in tropical Asia. III. The effects of land clearing through burning on fertility level. Agric. Ecosyst. Environ. 19 , 311–332 (1987).

Dechert, G., Veldkamp, E. & Brumme, R. Are partial nutrient balances suitable to evaluate nutrient sustainability of land use systems? Results from a case study in Central Sulawesi, Indonesia. Nutr. Cycling Agroecosyst. 72 , 201–212 (2005).

Neill, C. et al. Soil carbon and nitrogen stocks following forest clearing for pasture in the southwestern Brazilian Amazon. Ecol. Appl. 7 , 1216–1225 (1997).

Allen, K., Corre, M. D., Kurniawan, S., Utami, S. R. & Veldkamp, E. Spatial variability surpasses land-use change effects on soil biochemical properties of converted lowland landscapes in Sumatra, Indonesia. Geoderma 284 , 42–50 (2016).

Carlson, K. M. et al. Effect of oil palm sustainability certification on deforestation and fire in Indonesia. Proc. Natl Acad. Sci. USA 115 , 121–126 (2018).

Sanchez P. A. & Logan T. J. Myths and Science About the Chemistry and Fertility of Soils in the Tropics (Soil Science Society of America and American Society of Agronomy, 1992).

Stahl, C. et al. Continuous soil carbon storage of old permanent pastures in Amazonia. Glob. Change Biol. 23 , 3382–3392 (2017).

Bautista-Cruz, A. & del Castillo, R. F. Soil changes during secondary succession in a tropical montane cloud forest area. Soil Sci. Soc. Am. J. 69 , 906–914 (2005).

Marin-Spiotta, E., Silver, W. L., Swanston, C. W. & Ostertag, R. Soil organic matter dynamics during 80 years of reforestation of tropical pastures. Glob. Change Biol. 15 , 1584–1597 (2009).

Silver, W. L. et al. Effects of soil texture on belowground carbon and nutrient storage in a lowland Amazonian forest ecosystem. Ecosystems 3 , 193–209 (2000).

Oades, J. & Waters, A. Aggregate hierarchy in soils. Soil Res. 29 , 815–828 (1991).

Chauvel, A., Grimaldi, M. & Tessier, D. Changes in soil pore-space distribution following deforestation and revegetation: an example from the Central Amazon Basin, Brazil. For. Ecol. Manag. 38 , 259–271 (1991).

Kayombo, B. & Lal, R. Effects of soil compaction by rolling on soil structure and development of maize in no-till and disc ploughing systems on a tropical alfisol. Soil. Tillage Res. 7 , 117–134 (1986).

Lal, R. Effects of macrofauna on soil properties in tropical ecosystems. Agric. Ecosyst. Environ. 24 , 101–116 (1988).

Ghuman, B. S., Lal, R. & Shearer, W. Land clearing and use in the humid Nigerian tropics: I. Soil physical properties. Soil Sci. Soc. Am. J. 55 , 178–183 (1991).

Minasny, B. & Hartemink, A. E. Predicting soil properties in the tropics. Earth Sci. Rev. 106 , 52–62 (2011).

Hombegowda, H. C., van Straaten, O., Köhler, M. & Hölscher, D. On the rebound: soil organic carbon stocks can bounce back to near forest levels when agroforests replace agriculture in southern India. SOIL 2 , 13–23 (2016).

Parton, W. J., Stewart, J. W. B. & Cole, C. V. Dynamics of C, N, P and S in grassland soils: a model. Biogeochemistry 5 , 109–131 (1988).

López-Ulloa, M., Veldkamp, E. & de Koning, G. H. J. Soil carbon stabilization in converted tropical pastures and forests depends on soil type. Soil Sci. Soc. Am. J. 69 , 1110–1117 (2005).

Paul, S., Flessa, H., Veldkamp, E. & López-Ulloa, M. Stabilization of recent soil carbon in the humid tropics following land use changes: evidence from aggregate fractionation and stable isotope analyses. Biogeochemistry 87 , 247–263 (2008).

Amundson, R. The carbon budget in soils. Annu. Rev. Earth Planet. Sci. 29 , 535–562 (2001).

Douglas, P. M. J. et al. A long-term decrease in the persistence of soil carbon caused by ancient Maya land use. Nat. Geosci. 11 , 645–649 (2018).

Marín-Spiotta, E. & Sharma, S. Carbon storage in successional and plantation forest soils: a tropical analysis. Glob. Ecol. Biogeogr. 22 , 105–117 (2013).

Trumbore, S. E., Davidson, E. A., Barbosa de Camargo, P., Nepstad, D. C. & Martinelli, L. A. Belowground cycling of carbon in forests and pastures of eastern Amazonia. Glob. Biogeochem. Cycles 9 , 515–528 (1995).

Veldkamp, E., Becker, A., Schwendenmann, L., Clark, D. A. & Schulte-Bisping, H. Substantial labile carbon stocks and microbial activity in deeply weathered soils below a tropical wet forest. Glob. Change Biol. 9 , 1171–1184 (2003).

Intergovernmental Panel on Climate Change (IPCC) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019).

Reiners, W. A., Bouwman, A. F., Parsons, W. F. J. & Keller, M. Tropical rain forest conversion to pasture: changes in vegetation and soil properties. Ecol. Appl. 4 , 363–377 (1994).

Hamer, U., Potthast, K., Burneo, J. I. & Makeschin, F. Nutrient stocks and phosphorus fractions in mountain soils of Southern Ecuador after conversion of forest to pasture. Biogeochemistry 112 , 495–510 (2013).

Veldkamp, E., Davidson, E., Erickson, H., Keller, M. & Weitz, A. Soil nitrogen cycling and nitrogen oxide emissions along a pasture chronosequence in the humid tropics of Costa Rica. Soil Biol. Biochem. 31 , 387–394 (1999).

Wick, B., Veldkamp, E., de Mello, W. Z., Keller, M. & Crill, P. Nitrous oxide fluxes and nitrogen cycling along a pasture chronosequence in Central Amazonia, Brazil. Biogeosciences 2 , 175–187 (2005).

van Dam, D., van Breemen, N. & Veldkamp, E. Soil organic carbon dynamics: variability with depth in forested and deforested soils under pasture in Costa Rica. Biogeochemistry 39 , 343–375 (1997).

Fisher, M. J. et al. Carbon storage by introduced deep-rooted grasses in the South American savannas. Nature 371 , 236–238 (1994).

Navarrete, D., Sitch, S., Aragão, L. E. O. C. & Pedroni, L. Conversion from forests to pastures in the Colombian Amazon leads to contrasting soil carbon dynamics depending on land management practices. Glob. Change Biol. 22 , 3503–3517 (2016).

Chiti, T., Grieco, E., Perugini, L., Rey, A. & Valentini, R. Effect of the replacement of tropical forests with tree plantations on soil organic carbon levels in the Jomoro district, Ghana. Plant Soil 375 , 47–59 (2014).

Kirsten, M., Kimaro, D. N., Feger, K.-H. & Kalbitz, K. Impact of land use on soil organic carbon stocks in the humid tropics of NE Tanzania. J. Plant. Nutr. Soil Sci. 182 , 625–636 (2019).

Kassa, H., Dondeyne, S., Poesen, J., Frankl, A. & Nyssen, J. Impact of deforestation on soil fertility, soil carbon and nitrogen stocks: the case of the Gacheb catchment in the White Nile Basin, Ethiopia. Agric. Ecosyst. Environ. 247 , 273–282 (2017).

Dechert, G., Veldkamp, E. & Anas, I. Is soil degradation unrelated to deforestation? Examining soil parameters of land use systems in upland Central Sulawesi, Indonesia. Plant Soil 265 , 197–209 (2004).

Hiremath, A. J. & Ewel, J. J. Ecosystem nutrient use efficiency, productivity, and nutrient accrual in model tropical communities. Ecosystems 4 , 669–682 (2001).

Pineiro, G., Oesterheld, M., Batista, W. B. & Paruelo, J. M. Opposite changes of whole-soil vs. pools C:N ratios: a case of Simpson’s paradox with implications on nitrogen cycling. Glob. Change Biol. 12 , 804–809 (2006).

de Koning, G. H. J., Veldkamp, E. & López-Ulloa, M. Quantification of carbon sequestration in soils following pasture to forest conversion in northwestern Ecuador. Glob. Biogeochem. Cycles 17 , 1098 (2003).

Silver, W. L., Ostertag, R. & Lugo, A. E. The potential for carbon sequestration through reforestation of abandoned tropical agricultural and pasture lands. Restor. Ecol. 8 , 394–407 (2000).

Krashevska, V. et al. Micro-decomposer communities and decomposition processes in tropical lowlands as affected by land use and litter type. Oecologia 187 , 255–266 (2018).

Allen, K., Corre, M. D., Tjoa, A. & Veldkamp, E. Soil nitrogen-cycling responses to conversion of lowland forests to oil palm and rubber plantations in Sumatra, Indonesia. PLoS ONE 10 , e0133325 (2015).

Brinkmann, N. et al. Intensive tropical land use massively shifts soil fungal communities. Sci. Rep. 9 , 3403 (2019).

Berkelmann, D. et al. How rainforest conversion to agricultural systems in Sumatra (Indonesia) affects active soil bacterial communities. Front. Microbiol. 9 , 2381 (2018).

Schneider, D. et al. Impact of lowland rainforest transformation on diversity and composition of soil prokaryotic communities in Sumatra (Indonesia). Front. Microbiol. 6 , 1339 (2015).

Janos, D. P. Mycorrhizae influence tropical succession. Biotropica 12 , 56–64 (1980).

Bachelot, B. et al. Associations among arbuscular mycorrhizal fungi and seedlings are predicted to change with tree successional status. Ecology 99 , 607–620 (2018).

Gei, M. et al. Legume abundance along successional and rainfall gradients in Neotropical forests. Nat. Ecol. Evol. 2 , 1104–1111 (2018).

Ostertag, R., Marín-Spiotta, E., Silver, W. L. & Schulten, J. Litterfall and decomposition in relation to soil carbon pools along a secondary forest chronosequence in Puerto Rico. Ecosystems 11 , 701–714 (2008).

Cole, R. J., Selmants, P., Khan, S. & Chazdon, R. Litter dynamics recover faster than arthropod biodiversity during tropical forest succession. Biotropica 52 , 22–33 (2020).

Zou, X. & Gonzalez, G. Changes in earthworm density and community structure during secondary succession in abandoned tropical pastures. Soil Biol. Biochem. 29 , 627–629 (1997).

Stone, M. J., Shoo, L., Stork, N. E., Sheldon, F. & Catterall, C. P. Recovery of decomposition rates and decomposer invertebrates during rain forest restoration on disused pasture. Biotropica 52 , 230–241 (2020).

Meloni, F. & Varanda, E. M. Litter and soil arthropod colonization in reforested semi-deciduous seasonal Atlantic forests: Arthropod colonization in Atlantic forest soils. Restor. Ecol. 23 , 690–697 (2015).

Cleveland, C. C. et al. Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis: Nutrients, climate and tropical NPP. Ecol. Lett. 14 , 939–947 (2011).

Matson, A. L., Corre, M. D., Burneo, J. I. & Veldkamp, E. Free-living nitrogen fixation responds to elevated nutrient inputs in tropical montane forest floor and canopy soils of southern Ecuador. Biogeochemistry 122 , 281–294 (2015).

Hedin, L. O., Brookshire, E. N. J., Menge, D. N. L. & Barron, A. R. The nitrogen paradox in tropical forest ecosystems. Annu. Rev. Ecol. Evol. Syst. 40 , 613–635 (2009).

Cusack, D. F., Silver, W. & McDowell, W. H. Biological nitrogen fixation in two tropical forests: ecosystem-level patterns and effects of nitrogen fertilization. Ecosystems 12 , 1299–1315 (2009).

Kaspari, M. & Powers, J. S. Biogeochemistry and geographical ecology: Embracing all twenty-five elements required to build organisms. Am. Nat. 188 , S62–S73 (2016).

Kennedy, M. J., Chadwick, O. A., Vitousek, P. M., Derry, L. A. & Hendricks, D. M. Changing sources of base cations during ecosystem development, Hawaiian Islands. Geology 26 , 1015–1018 (1998).

Bristow, C. S., Hudson-Edwards, K. A. & Chappell, A. Fertilizing the Amazon and equatorial Atlantic with West African dust. Geophys. Res. Lett. 37 , L14807 (2010).

Bortoluzzi, E. C., Pérez, C. A. S., Ardisson, J. D., Tiecher, T. & Caner, L. Occurrence of iron and aluminum sesquioxides and their implications for the P sorption in subtropical soils. Appl. Clay Sci. 104 , 196–204 (2015).

Hedin, L. O., Vitousek, P. M. & Matson, P. A. Nutrient losses over four million years of tropical forest development. Ecology 84 , 2231–2255 (2003).

Mackensen, J., Hölscher, D., Klinge, R. & Fölster, H. Nutrient transfer to the atmosphere by burning of debris in eastern Amazonia. For. Ecol. Manag. 86 , 121–128 (1996).

Klinge, R., Araujo Martins, A. R., Mackensen, J. & Fölster, H. Element loss on rain forest conversion in East Amazonia: comparison of balances of stores and fluxes. Biogeochemistry 69 , 63–82 (2004).

Weitz, A. M., Veldkamp, E., Keller, M., Neff, J. & Crill, P. M. Nitrous oxide, nitric oxide, and methane fluxes from soils following clearing and burning of tropical secondary forest. J. Geophys. Res. Atmos. 103 , 28047–28058 (1998).

Moebius-Clune, B. N. et al. Long-term soil quality degradation along a cultivation chronosequence in western Kenya. Agric. Ecosyst. Environ. 141 , 86–99 (2011).

Ngoze, S. et al. Nutrient constraints to tropical agroecosystem productivity in long-term degrading soils. Glob. Change Biol. 14 , 2810–2822 (2008).

Haileslassie, A., Priess, J. A., Veldkamp, E. & Lesschen, J. P. Nutrient flows and balances at the field and farm scale: Exploring effects of land-use strategies and access to resources. Agric. Syst. 94 , 459–470 (2007).

Kassa, H., Dondeyne, S., Poesen, J., Frankl, A. & Nyssen, J. Agro-ecological implications of forest and agroforestry systems conversion to cereal-based farming systems in the White Nile Basin, Ethiopia. Agroecol. Sustain. Food Syst. 42 , 149–168 (2018).

Jobbágy, E. G. & Jackson, R. B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10 , 423–436 (2000).

Sanderman, J., Hengl, T. & Fiske, G. J. Soil carbon debt of 12,000 years of human land use. Proc. Natl Acad. Sci. USA 114 , 9575–9580 (2017).

Drake, T. W. et al. Mobilization of aged and biolabile soil carbon by tropical deforestation. Nat. Geosci. 12 , 541–546 (2019).

Meijide, A. et al. Measured greenhouse gas budgets challenge emission savings from palm-oil biodiesel. Nat. Commun. 11 , 1089 (2020).

Conrad, R. Microbial ecology of methanogens and methanotrophs. Adv. Agron. 96 , 1–63 (2007).

Dutaur, L. & Verchot, L. V. A global inventory of the soil CH 4 sink. Glob. Biogeochem. Cycles 21 , GB4013 (2007).

Veldkamp, E., Koehler, B. & Corre, M. D. Indications of nitrogen-limited methane uptake in tropical forest soils. Biogeosciences 10 , 5367–5379 (2013).

Matson, A. L., Corre, M. D., Langs, K. & Veldkamp, E. Soil trace gas fluxes along orthogonal precipitation and soil fertility gradients in tropical lowland forests of Panama. Biogeosciences 14 , 3509–3524 (2017).

Koehler, B. et al. An in-depth look into a tropical lowland forest soil: nitrogen-addition effects on the contents of N 2 O, CO 2 and CH 4 and N 2 O isotopic signatures down to 2-m depth. Biogeochemistry 111 , 695–713 (2012).

Hassler, E. et al. Soil fertility controls soil–atmosphere carbon dioxide and methane fluxes in a tropical landscape converted from lowland forest to rubber and oil palm plantations. Biogeosciences 12 , 5831–5852 (2015).

Keller, M. & Reiners, W. A. Soil-atmosphere exchange of nitrous oxide, nitric oxide, and methane under secondary succession of pasture to forest in the Atlantic lowlands of Costa Rica. Glob. Biogeochem. Cycles 8 , 399–409 (1994).

Veldkamp, E., Weitz, A. M. & Keller, M. Management effects on methane fluxes in humid tropical pasture soils. Soil Biol. Biochem. 33 , 1493–1499 (2001).

Tian, H. et al. Global methane and nitrous oxide emissions from terrestrial ecosystems due to multiple environmental changes. Ecosyst. Health Sustain. 1 , 1–20 (2015).

Veldkamp, E., Purbopuspito, J., Corre, M. D., Brumme, R. & Murdiyarso, D. Land use change effects on trace gas fluxes in the forest margins of Central Sulawesi, Indonesia. J. Geophys. Res. Biogeosci. 113 , G02003 (2008).

Weitz, A. M., Linder, E., Frolking, S., Crill, P. M. & Keller, M. N 2 O emissions from humid tropical agricultural soils: effects of soil moisture, texture and nitrogen availability. Soil. Biol. Biochem. 33 , 1077–1093 (2001).

Keesstra, S. et al. Soil as a filter for groundwater quality. Curr. Opin. Environ. Sustain. 4 , 507–516 (2012).

Schwendenmann, L. & Veldkamp, E. The role of dissolved organic carbon, dissolved organic nitrogen, and dissolved inorganic nitrogen in a tropical wet forest ecosystem. Ecosystems 8 , 339–351 (2005).

Lehmann, J. et al. Subsoil retention of organic and inorganic nitrogen in a Brazilian savanna Oxisol. Soil Use Manag. 20 , 163–172 (2004).

Neill, C. et al. Watershed responses to Amazon soya bean cropland expansion and intensification. Philos. Trans. R. Soc. B Biol. Sci. 368 , 20120425 (2013).

Rasiah, V. & Armour, J. D. Nitrate accumulation under cropping in the Ferrosols of Far North Queensland wet tropics. Aust. J. Soil Res. 39 , 329–341 (2001).

Goller, R., Wilcke, W., Fleischbein, K., Valarezo, C. & Zech, W. Dissolved nitrogen, phosphorus, and sulfur forms in the ecosystem fluxes of a montane forest in Ecuador. Biogeochemistry 77 , 57–89 (2006).

Aragão, L. E. O. C. The rainforest’s water pump. Nature 489 , 217–218 (2012).

Spracklen, D. V., Arnold, S. R. & Taylor, C. M. Observations of increased tropical rainfall preceded by air passage over forests. Nature 489 , 282–285 (2012).

Giertz, S., Junge, B. & Diekkrüger, B. Assessing the effects of land use change on soil physical properties and hydrological processes in the sub-humid tropical environment of West Africa. Phys. Chem. Earth Parts A/B/C 30 , 485–496 (2005).

Davidson, E. A. et al. The Amazon basin in transition. Nature 481 , 321–328 (2012).

Kassa, H., Frankl, A., Dondeyne, S., Poesen, J. & Nyssen, J. Sediment yield at southwest Ethiopia’s forest frontier. Land Degrad. Dev. 30 , 695–705 (2019).

Molina, A., Vanacker, V., Balthazar, V., Mora, D. & Govers, G. Complex land cover change, water and sediment yield in a degraded Andean environment. J. Hydrol. 472–473 , 25–35 (2012).

Labrière, N., Locatelli, B., Laumonier, Y., Freycon, V. & Bernoux, M. Soil erosion in the humid tropics: A systematic quantitative review. Agric. Ecosyst. Environ. 203 , 127–139 (2015).

Islam, K. R. & Weil, R. R. Land use effects on soil quality in a tropical forest ecosystem of Bangladesh. Agric. Ecosyst. Environ. 79 , 9–16 (2000).

Le Bissonnais, Y. et al. Soil aggregate stability in Mediterranean and tropical agro-ecosystems: effect of plant roots and soil characteristics. Plant Soil 424 , 303–317 (2018).

Garcı́a-Oliva, F., Sanford, R. L. & Kelly, E. Effects of slash-and-burn management on soil aggregate organic C and N in a tropical deciduous forest. Geoderma 88 , 1–12 (1999).

Sidle, R. C. et al. Erosion processes in steep terrain — Truths, myths, and uncertainties related to forest management in Southeast Asia. For. Ecol. Manag. 224 , 199–225 (2006).

Nagy, R. C. et al. Soil carbon dynamics in soybean cropland and forests in Mato Grosso, Brazil. J. Geophys. Res. Biogeosci. 123 , 18–31 (2018).

Driessen, P. M. Lecture Notes on the Major Soils of the World (Food and Agriculture Organization of the United Nations, 2001).

Tisdall, J. M. & Oades, J. M. Organic matter and water-stable aggregates in soils. J. Soil. Sci. 33 , 141–163 (1982).

Haileslassie, A., Priess, J., Veldkamp, E., Teketay, D. & Lesschen, J. P. Assessment of soil nutrient depletion and its spatial variability on smallholders’ mixed farming systems in Ethiopia using partial versus full nutrient balances. Agric. Ecosyst. Environ. 108 , 1–16 (2005).

Quinton, J. N., Govers, G., Van Oost, K. & Bardgett, R. D. The impact of agricultural soil erosion on biogeochemical cycling. Nat. Geosci. 3 , 311–314 (2010).

Amundson, R. et al. Soil and human security in the 21st century. Science 348 , 1261071 (2015).

Powers, J. S. & Marín-Spiotta, E. Ecosystem processes and biogeochemical cycles in secondary tropical forest succession. Annu. Rev. Ecol. Evol. Syst. 48 , 497–519 (2017).

Russell, A. E. & Raich, J. W. Rapidly growing tropical trees mobilize remarkable amounts of nitrogen, in ways that differ surprisingly among species. Proc. Natl. Acad. Sci. USA 109 , 10398–10402 (2012).

Saynes, V., Hidalgo, C., Etchevers, J. D. & Campo, J. E. Soil C and N dynamics in primary and secondary seasonally dry tropical forests in Mexico. Appl. Soil. Ecol. 29 , 282–289 (2005).

Barron, A. R. et al. Molybdenum limitation of asymbiotic nitrogen fixation in tropical forest soils. Nat. Geosci. 2 , 42–45 (2009).

Szott, L. T., Palm, C. A. & Buresh, R. J. Ecosystem fertility and fallow function in the humid and subhumid tropics. Agrofor. Syst. 47 , 163–196 (1999).

Batterman, S. A. et al. Key role of symbiotic dinitrogen fixation in tropical forest secondary succession. Nature 502 , 224–227 (2013).

Lawrence, D. & Schlesinger, W. H. Changes in soil phosphorus during 200 years of shifting cultivation in Indonesia. Ecology 82 , 2769–2780 (2001).

Markewitz, D., Figueiredo, R., de, O. & Davidson, E. A. CO 2 -driven cation leaching after tropical forest clearing. J. Geochem. Explor. 88 , 214–219 (2006).

Markewitz, D. et al. Control of cation concentrations in stream waters by surface soil processes in an Amazonian watershed. Nature 410 , 802–805 (2001).

Orihuela-Belmonte, D. E. et al. Carbon stocks and accumulation rates in tropical secondary forests at the scale of community, landscape and forest type. Agric. Ecosyst. Environ. 171 , 72–84 (2013).

Davidson, E. A. et al. Nitrogen and phosphorus limitation of biomass growth in a tropical secondary forest. Ecol. Appl. 14 , 150–163 (2004).

Lu, D., Moran, E. & Mausel, P. Linking Amazonian secondary succession forest growth to soil properties. Land Degrad. Dev. 13 , 331–343 (2002).

Mekuria, W., Veldkamp, E., Corre, M. D. & Haile, M. Restoration of ecosystem carbon stocks following exclosure establishment in communal grazing lands in Tigray, Ethiopia. Soil Sci. Soc. Am. J. 75 , 246–256 (2011).

Shi, Z. et al. The age distribution of global soil carbon inferred from radiocarbon measurements. Nat. Geosci. 13 , 555–559 (2020).

Palm, C. A. et al. Nitrous oxide and methane fluxes in six different land use systems in the Peruvian Amazon. Glob. Biogeochem. Cycles 16 , 1073 (2002).

Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W. & Vertessy, R. A. A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation. J. Hydrol. 310 , 28–61 (2005).

Ogden, F. L., Crouch, T. D., Stallard, R. F. & Hall, J. S. Effect of land cover and use on dry season river runoff, runoff efficiency, and peak storm runoff in the seasonal tropics of Central Panama. Water Resour. Res. 49 , 8443–8462 (2013).

Lacombe, G. et al. Contradictory hydrological impacts of afforestation in the humid tropics evidenced by long-term field monitoring and simulation modelling. Hydrol. Earth Syst. Sci. 20 , 2691–2704 (2016).

de Blécourt, M., Gröngröft, A., Baumann, S. & Eschenbach, A. Losses in soil organic carbon stocks and soil fertility due to deforestation for low-input agriculture in semi-arid southern Africa. J. Arid. Environ. 165 , 88–96 (2019).

Garcin, Y. et al. Early anthropogenic impact on Western Central African rainforests 2,600 y ago. Proc. Natl Acad. Sci. USA 115 , 3261–3266 (2018).

Bayon, G. et al. Intensifying weathering and land use in Iron Age Central Africa. Science 335 , 1219–1222 (2012).

Beach, T., Dunning, N., Luzzadder-Beach, S., Cook, D. E. & Lohse, J. Impacts of the ancient Maya on soils and soil erosion in the central Maya Lowlands. Catena 65 , 166–178 (2006).

Lombardo, U. & Prümers, H. Pre-Columbian human occupation patterns in the eastern plains of the Llanos de Moxos, Bolivian Amazonia. J. Archaeol. Sci. 37 , 1875–1885 (2010).

Arroyo-Kalin, M. The Amazonian formative: crop domestication and anthropogenic soils. Diversity 2 , 473–504 (2010).

Glaser, B. & Birk, J. J. State of the scientific knowledge on properties and genesis of Anthropogenic Dark Earths in Central Amazonia ( terra preta de Índio ). Geochim. Cosmochim. Acta 82 , 39–51 (2012).

Richter, D. D. & Markewitz, D. How deep is soil? BioScience 45 , 600–609 (1995).

Borneman, J. & Triplett, E. W. Molecular microbial diversity in soils from eastern Amazonia: evidence for unusual microorganisms and microbial population shifts associated with deforestation. Appl. Environ. Microbiol. 63 , 2647–2653 (1997).

Powers, J. S. & Veldkamp, E. Regional variation in soil carbon and δ 13 C in forests and pastures of northeastern Costa Rica. Biogeochemistry 72 , 315–336 (2005).

Lucas, Y. The role of plants in controlling rates and products of weathering: importance of biological pumping. Annu. Rev. Earth Planet. Sci. 29 , 135–163 (2001).

Kleber, M., Schwendenmann, L., Veldkamp, E., Rößner, J. & Jahn, R. Halloysite versus gibbsite: Silicon cycling as a pedogenetic process in two lowland neotropical rain forest soils of La Selva, Costa Rica. Geoderma 138 , 1–11 (2007).

Lucas, Y., Luizao, F. J., Chauvel, A., Rouiller, J. & Nahon, D. The relation between biological activity of the rain forest and mineral composition of soils. Science 260 , 521–523 (1993).

Bouma, J. et al. Hydropedological insights when considering catchment classification. Hydrol. Earth Syst. Sci. 15 , 1909–1919 (2011).

Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Glob. Biogeochem. Cycles 19 , GB1015 (2005).

Jenny, H. Factors of Soil Formation. A System of Quantitative Pedology (McGraw-Hill, 1941).

de Blécourt, M., Brumme, R., Xu, J., Corre, M. D. & Veldkamp, E. Soil carbon stocks decrease following conversion of secondary forests to rubber ( Hevea brasiliensis ) plantations. PLoS ONE 8 , e69357 (2013).

Darras, K. F. A. et al. Reducing fertilizer and avoiding herbicides in oil palm plantations — Ecological and economic valuations. Front. For. Glob. Change 2 , 65 (2019).

Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342 , 850–853 (2013).

Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12 , e0169748 (2017).

IUSS Working Group WRB. World Reference Base for Soil Resources 2014. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps (FAO, 2015).

FAO. Global Forest Resources Assessment 2015: How are the World’s Forests Changing? (FAO, 2016).

Saikh, H., Varadachari, C. & Ghosh, K. Changes in carbon, nitrogen and phosphorus levels due to deforestation and cultivation: a case study in Simlipal National Park, India. Plant Soil 198 , 137–145 (1998).

Paul, S., Veldkamp, E. & Flessa, H. Differential response of mineral-associated organic matter in tropical soils formed in volcanic ashes and marine Tertiary sediment to treatment with HCl, NaOCl, and Na 4 P 2 O 7 . Soil Biol. Biochem. 40 , 1846–1855 (2008).

Soil Survey Staff. Keys to Soil Taxonomy (US Department of Agriculture, Natural Resources Conservation Service, 2014).

Foley, J. A. et al. Solutions for a cultivated planet. Nature 478 , 337–342 (2011).

Alston, L. J., Libecap, G. D. & Mueller, B. Land reform policies, the sources of violent conflict, and implications for deforestation in the Brazilian Amazon. J. Environ. Econ. Manag. 39 , 162–188 (2000).

Gatto, M., Wollni, M. & Qaim, M. Oil palm boom and land-use dynamics in Indonesia: The role of policies and socioeconomic factors. Land Use Policy 46 , 292–303 (2015).

Jantalia, C. P. et al. Tillage effect on C stocks of a clayey Oxisol under a soybean-based crop rotation in the Brazilian Cerrado region. Soil Tillage Res. 95 , 97–109 (2007).

Six, J. et al. Soil organic matter, biota and aggregation in temperate and tropical soils - Effects of no-tillage. Agronomie 22 , 755–775 (2002).

Comte, I. et al. Physicochemical properties of soils in the Brazilian Amazon following fire-free land preparation and slash-and-burn practices. Agric. Ecosyst. Environ. 156 , 108–115 (2012).

Abu Bakar, R., Darus, S. Z., Kulaseharan, S. & Jamaluddin, N. Effects of ten year application of empty fruit bunches in an oil palm plantation on soil chemical properties. Nutr. Cycling Agroecosyst. 89 , 341–349 (2011).

Clay, D., Reardon, T. & Kangasniemi, J. Sustainable intensification in the highland tropics: Rwandan farmers’ investments in land conservation and soil fertility. Econ. Dev. Cult. Change 46 , 351–377 (1998).

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Acknowledgements

We thank the following researchers for providing their original data from their publications: Marleen de Blécourt; Tommaso Chiti, Ute Hamer, Hennok Kassa, Maximilian Kirsten, Wolde Mekuria, Diego Navarrete, Jan Nyssen, Iván Prieto, Amin Soltangheisi, Clément Stahl and Oliver van Straaten. We thank Oliver van Straaten for making the maps. We thank Boniface Massawe for assistance with the soil profile images. E.V. and M.D.C. acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation — Project ID 192626868 — SFB 990) as part of project A05.

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Supplementary information

Supplementary information.

Cutting down and burning of vegetation in an area, often as preparation for agricultural use.

Agricultural system in which the area is fallowed in between periods of cultivation, allowing natural vegetation to return and soils to recover.

Time during which arable land is not actively used in crop production.

Removal of forest and conversion of land for other uses.

Re-establishment of forest after disturbance.

Ecological changes during the regeneration of an ecosystem on disturbed or damaged land.

Native forests that lack substantial signs of human activity or disturbance, sometimes referred to as old-growth forest.

Soil properties that change with disturbances and management.

Uppermost layer of soil, specifically, the top 10 cm for this Review.

Soil layers >10 cm; deeper subsoils refers to >50 cm for this Review.

(ECEC). Negatively charged sites in the soil that adsorb exchangeable cations, measured at field pH.

Treatment of soil with lime, with the goal of reducing acidity.

Forests established after the removal or disturbance of the original (primary) forests.

Composition of soil in terms of sand, silt and clay.

Growth of trees or shrubs and crop products concurrently.

Total amount of biomass in an area.

The biomass produced per unit of nutrients taken up by plants.

Number of species in a community.

Organism that feeds on dead biomass.

Receiving nutrients by exchanging resources with host cells.

Symbiotic relationship between plant and fungus in a rooting system.

Receiving nutrients by breaking down dead host cells.

Receiving nutrients by harming host cells.

Downed vegetation produced during slash-and-burn management.

Microbial process where nitrate (NO 3 − ) is reduced to NO, N 2 O and, ultimately, N 2 .

(AEC). Positively charged sites in the soil that adsorb exchangeable anions.

Oxides with three oxygen atoms for every two atoms of another element, mostly as aluminium oxide (Al 2 O 3 ) or iron oxide (Fe 2 O 3 ) in soils.

One-sided green leaf area per unit ground area, used as a measure of greenness and vegetation.

Microbial process where organic N or ammonia is oxidized to nitrate.

Removal of soil by water (as opposed to wind, for example).

Studying ecological processes at different aged sites, assumed to represent different stages of developments; used especially in studies of long-term processes.

Plants that use the C 4 carbon-fixation pathway, as opposed to the C 3 carbon-fixation pathway.

Layered silicate clays formed through the weathering of aluminium silicates with the formula Al 2 Si 2 O 5 (OH) 4 .

An aluminium-hydroxide mineral, with the formula Al(OH) 3 .

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Veldkamp, E., Schmidt, M., Powers, J.S. et al. Deforestation and reforestation impacts on soils in the tropics. Nat Rev Earth Environ 1 , 590–605 (2020). https://doi.org/10.1038/s43017-020-0091-5

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A review of the environmental Kuznets curve hypothesis for deforestation policy in Bangladesh

iForest - Biogeosciences and Forestry, Volume 4 , Issue 1 , Pages 16-24 (2011) doi: https://doi.org/10.3832/ifor0558-004 Published: Jan 27, 2011 - Copyright © 2011 SISEF

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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. The dictation of national economic growth to deforestation can be found through the study of EKC. To understand the EKC phenomena for deforestation, the study was undertaken through reviewing the literature. With the understanding of the different EKC trajectories for deforestation, an attempt was made to implicate the economic development of Bangladesh with the EKC. The proven EKC trajectories for deforestation in some regions/countries show a higher income per capita requirement for the turning point. The study suggests that tunneling in the EKC trajectory for Bangladesh would be favorable. The type of economic and forest policy that Bangladesh should follow to retard deforestation is also revealed. Clean Development Mechanism (CDM) and Reducing Emissions from Deforestation and forest Degradation (REDD) have been suggested for tunneling the EKC in Bangladesh. The findings of the study are expected to contribute to the environmental development of Bangladesh.

CDM , Climate change , Economic growth , EKC , REDD+ , Slowing deforestation

  Introduction 

Deforestation in the developing countries is one of the most serious environmental concerns because of the resulting biodiversity loss, soil degradation and significant contribution to global climate change, etc. ( [19] ). The economic activities of a nation including its livelihood and cultural integrity are also affected by the degradation ( [14] ). The quick deforestation in the tropical zone has come into the limelight as a major source of global greenhouse gases (GHG). Fearnside & Laurance ( [23] ) report that tropical deforestation contributes from 0.8 Gt to 2.4 Gt (Gigatons: 1 Gt = 1 x 10 9 metric tons = 10 15 grams) to the total global annual GHG emissions, varying due to the uncertainty of the estimates and debates by different studies. Forests in the tropical zone, especially Asia and including Bangladesh, have become the most threatened region on the earth and have also been a significant source of GHGs ( [44] ). An increased amount of GHGs is considered the main cause of global warming, causing climate change. The most important GHGs are CO 2 , CH 4 , N 2 O, SOx, NOx and F-gases (gases that contain Fluorine).

Growth in Gross Domestic Product (GDP) or income per capita in a nation seems to be interlinked with environmental ups and downs. Where an economy develops by taking resources from the environment, after a certain point, an economy must help the environment to keep up both of their sustainability. The abatement activity starts after a substantial amount of capital stock is achieved ( [65] ). An Environmental Kuznets Curve (EKC) is a hypothesized relationship between economic growth (income per capita ) and environmental quality. This curve indicates that economic growth initially contributes to the degradation of environmental quality, but with further growth, the relationship is reversed and environmental degradation starts to decrease. This relationship provides an inverted U-shape curve, where environmental degradation first rises and then falls with increasing income per capita . The idea of EKC came into the limelight in 1991 with the study of NAFTA (North American Free Trade Agreement - [28] ), though the idea of Kuznets curve (relationship of economic growth and income inequality) existed from 1955 ( [42] ). However, the Environmental Kuznets curve (EKC) hypothesis became very important after 1991 for its potentiality and promise of finding a final solution to environmental degradation. Deforestation, an important phenomenon of environmental degradation, has already been shown to be subject to national economic growth in many countries. Koop & Tole ( [41] ) analyzed the economic distributional profile of a developing country on the forest loss. They found that an economy with greater inequality had more deforestation than that of an egalitarian economy. Rather, the egalitarian economy could ameliorate the negative impact of the economic growth on the forest. Mather ( [47] ) also studied the forest transition in some Asian countries, which proved the effect of economic growth on forests.

Bangladesh, a south Asian least developed country, has been experiencing severe deforestation over the last 3 to 4 decades. Still, Bangladesh has not found any effective way to halt the deforestation. It hypothesizes that Bangladesh is presently at the initial up-facing stage of EKC considering deforestation. Many studies were found to judge the EKC for deforestation in different developing countries ( [40] , [7] , [20] ). While studying the economic impacts on deforestation at a global level, Scrieciu ( [63] ) concluded that case-specific factors might influence deforestation in different countries and socio-geographic zones. Therefore, he focused his research on a more disaggregate, local level. However, there is no validly published study of EKC on deforestation in Bangladesh. This study aimed at relating the results of EKC for other developing countries with Bangladesh. What will be the fate of the deforestation of Bangladesh in regards to ongoing economic development? Will Bangladesh follow the inverted U-shape of the EKC? If yes, what should be the economic and environmental policy to retard deforestation within a shorter period? We expect this paper will contribute significantly to this environmental issue. The findings of the study would be of immense importance for the forestry development in Bangladesh.

Bangladesh forestry sector: general overview

Bangladesh is a south Asian least developed country located between 20° 34’ to 26° 38’ N latitude and 88° 01’ to 92#176; 42’ E longitude with a geographical coverage of 14.76 M ha with three broad categories of land-hills, uplifted land blocks and alluvial plains ( [6] ). The country is characterized by low per capita gross national product; low natural resource base; high population density, and high incidence of natural disasters. The climate is subtropical, characterized by high temperature, heavy rainfall, often-excessive humidity, and marked seasonal variations. There are three main seasons: (1) a hot summer season, with high temperatures (5-10 days of more than 40 °C maximum in the west), highest rate of evaporation, and erratic but heavy rainfall from March through June; (2) a hot and humid monsoon season (temperatures ranging from 20 to 36 °C), with heavy rainfall from June through October (about two-thirds of the mean annual rainfall); and (3) a relatively cooler and drier winter from November through March (temperatures ranging from 8 to 15 °C), when minimum temperature can fall below 5 °C in the north, though frost is extremely rare ( [50] ). The mean annual rainfall varies widely within the country, according to geographical location, ranging from 1200 mm in the extreme west to 5800 mm in the east and northeast ( [51] ).

Forestry is an important sector in Bangladesh’s economy. Forestlands make up almost 18%, agricultural lands 64% and urban areas 8% of the total lands in Bangladesh ( [21] ). Other land uses account for the remainder. Total forestland area is 2.56 M ha, including officially classified and unclassified state lands, village forests and tea/rubber gardens. Most of the state forestland is degraded ( [10] , [32] , [52] ). Classified and unclassified forestland signifies an administrative or legal category, not necessarily areas with tree cover. Natural forest accounts for about 31% and forest plantations 13% of total forest areas. Shifting cultivation, illegal occupation and unproductive areas account for the remaining forestland ( [21] ). Presently, protected areas represent just over 5% of forestland. Bangladesh Forest Department is responsible for administering 65% of state forestland. Local District Commissioners (DC) administers the other government forestlands. The better quality natural forests and plantations in the government forestlands, excluding parks and sanctuaries (medium to good density), make up around 0.8 M ha, which is 5.8% of Bangladesh’s total area. The area included in the present protected area network is 0.12 M ha, equal to 5.2% of state forestland or less than 1% of Bangladesh’s total area ( [21] ). The hilly areas of Chittagong, the Chittagong Hill Tracts, Cox’s Bazar and the Sylhet Forest divisions consist of hill forests, which are subject to severe degradation due to overpopulation, shifting cultivation and extension of agriculture ( [61] ). There are two main types of forests in the hilly areas, i.e. , evergreen and deciduous. These forests may be subdivided into several subtypes based on altitude, soil, rainfall, and other factors. The evergreen forest is made up of tropical wet evergreen and tropical mixed evergreen. The deciduous forest consists of tropical moist deciduous and tropical open deciduous. Tropical mixed evergreen forest is the most important type, with the dominant trees, Dipterocarps , being highly valued due to their high-priced timber. In the forests of the hilly areas, more than 100 evergreen and deciduous tree species have been identified as growing naturally ( [61] ).

During the period 2000-2005, the annual rate of deforestation in Bangladesh was 0.3% (2000 ha) as stated by FAO ( [22] ). Due to the deforestation, many plants and animals have become extinct or endangered in Bangladesh ( [10] ). A total of 40 inland mammals, 41 birds, 58 reptiles, 8 amphibians and 106 vascular plant species have reached at-risk status in varying magnitudes ( [34] , [37] ). Salam et al. ( [61] ) indicate that deforestation and degradation in the forests of Bangladesh are influenced by infra-structural problems related to the country’s underlying socioeconomic features. Salam et al. ( [61] ) divided the underlying factors into four sets of actors: (1) the indigenous forest dwellers, having their own problems (e.g., high population growth); (2) migrants, who move to the forests; (3) the timber industries cutting down too many trees; and (4) the government through its Forest Department which is not able or willing to implement suitable policies to regulate the cutting of trees and to prevent illegal cutting. Mitigating the first and second factors is a time-consuming task. The country is facing a high rate of population as a severe problem ( [55] , [46] ). The constantly increasing population and its growing consumption are expected to cause further loss of forest cover due to these first and second factors. In contrast, the third and fourth actors can be seen as a relative indulgence. The nature of the causes of forest loss in Bangladesh is such that any attempt to revert these trends will be ineffective without changes in the attitudes and practices of Forest Department officials and politicians with forest interests. The Forest Department has been losing its management capacity for many reasons, mostly related to the third and fourth actors.

  Method of the Study 

To explore the EKC trajectories for deforestation in relevance to Bangladesh, the study was conducted from August 2008 to August 2009. The data on global warming and its causes and consequences; EKC and behavior of deforestation in the EKC trajectory; and the socio-economic status of Bangladesh were collected mostly from the authoritative sources available on the Internet. Some facts were crosschecked directly in the offices of Bangladesh, mostly located at Dhaka and Chittagong. For researching the most recent facts, Scirus ( ⇒ http:/­/­www.­scirus.­com ), Scopus ( ⇒ http:/­/­www.­scopus.­com ) and ISI web of knowledge ( ⇒ http:/­/­apps.­isiknowledge.­com ) were used for reviewing the most relevant scientific articles. For that, some common keywords like economic growth, environmental degradation, deforestation, EKC and Kuznets curve were used to search out the specific articles. After selecting all the required articles, these were downloaded from the online sources. The downloaded articles were then printed out for the study. To establish a concrete understanding of the EKC regarding deforestation, many cross-references were also used.

As deforestation is the most important factor in global warming and major biodiversity loss in Bangladesh, it has been considered for understanding the EKC behavior. The most important findings on those parameters were synthesized, their specific research paradigms were compared and deviations among the results were discussed. The calculation of GDP and/or income per capita were considered for US$ at the specific period. The synthesis of the original scientific articles on EKC and different environmental degradations was used to implicate those for Bangladesh considering the national income and other drivers of EKC in Bangladesh.

  The EKC hypothesis and its general review 

The EKC curve shows that environmental degradation first increases with increasing income per capita, but that after a certain point in increasing income per capita, environmental degradation tends to diminish ( Fig. 1 ). Though environmental degradation rises quickly with a steep slope in the curve, its reduction gives a moderate slope. However, it gives a hill shaped curve by taking income per capita in X-axis as an independent variable and environmental degradation in Y-axis as a dependent variable. When there is no turning point in income per capita for any pollutant, the curve simply represents a straight line ( Fig. 1 ).

Fig. 1 - General environmental Kuznets Curve, (a) A full trajectory of inverted U-shape EKC; (b) Straight line of EKC, where no turning point is found.

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In some cases, an N-shaped EKC has also been found, i.e. , Bhattarai & Hammig ( [7] ) for deforestation, Torras & Boyce ( [75] ) for SOx emissions, etc. This happens when environmental degradation shows a positive, negative and positive relationship, respectively with income per capita. It means environmental degradation first increases with income per capita, but decreases after a certain level. This is how a peak is formed. Along with further increase in income per capita, degradation tends to rise again, which provides a trough in EKC ( Fig. 2 ).

Fig. 2 - Peaks and troughs of EKC.

In EKC relationship, the environment is like a luxury good ( [24] ). At the early stage of development, the environment is not really taken care of, but when income reaches a certain level, people want to act smart for the environment. However, this relationship is not as automated as it seems. Grossman & Krueger ( [29] ) stated that it is “an induced policy response” and that it has some variables working on it.

Generally, the EKC measures economic effect on environmental degradation by two models, i.e. , Fixed Effect (FE) and Random Effect (RE). In the first model, all the variables remain constant except income per capita, where it only measures the changes in environmental degradation with the changing income per capita. In the second model, it measures other additional variables as a changing factor. It is certain that the result will be different, depending on the model used. For example, RE model has given a higher value for the turning point than FE model for NOx emissions ( [64] ). In addition to this, Grossman & Krueger ( [28] ) have found that FE model has shown a higher value for the turning point. Not only has the turning point differed with the chosen model, but the presence of the hill-shaped EKC depends on them as well. Similarly, Koop & Tole ( [40] ) have found a turning point for deforestation using FE model, but no statistically significant turning point is found using RE model.

It is obvious that when income per capita crosses a certain point, the nation attempts to invest in mitigation measures for the betterment of the environment (if society is fully aware of the environment and the new technology). In general, the idea of EKC assumes that environmental degradation has no effect on economic growth ( [72] ). Koop & Tole ( [41] ) and Mather ( [47] ) confirm the effect of national economic growth on tropical deforestation. Scrieciu ( [63] ) and Barbier & Burgess ( [4] ) conclude that national income’s effect on deforestation varies from region to region.

Several experts often argue the fate of developing and poor countries through the viewpoint of EKC. As EKC shows that economic growth is the only possible way to retard deforestation when will they achieve enough income per capita to reach turning point? However, Munasinghe ( [53] , [54] ) has hypothesized a tunnel through the EKC which will help developing countries to attain a lower turning point by adopting measures from the developed ones ( Fig. 3 ). He has shown three possible paths of economic development aligned with the environmental damages. Among them, an economy should look for an optimal path through which it will avoid severe or moderate distortions of its environment ( Fig. 4 ).

Fig. 3 - Tunneling through the Environmental Kuznets Curve.

Fig. 4 - Alternative path of development to reduce environmental damage.

  EKC for deforestation 

People use forest products at the early stage of development, but after a certain rise in income per capita, forest products are replaced with some other alternative products that do not exert any harm to the forest ( [14] ). Higher population growth and the consequent agricultural expansion significantly cause deforestation and this trend can be halted through vertical development of agriculture and constructing socio-political institutions ( [44] , [59] , [60] , [14] ). This development of agriculture can go forward at some point of increased national income. These are the basics of EKC consideration in deforestation. The idea depends on several factors. Forest biomass fuels, especially firewood collected from forests, have been found to be universally dominant, especially in rural areas of the developing countries ( [3] ). In many countries, household income has been found to be the major driving force for determining the type of preferred energy carrier. (e.g., [30] , [31] , [35] ). In addition to this, “Energy Ladder Hypothesis” shows how the households shifts from using apparently dirty fuels to efficient clean fuels with the improvement of socio-economic conditions, especially income ( [2] , [15] , [45] , [16] ). Thus, fuel-wood use is assumed to be reduced with increasing income per capita by replacing it with modern energies, e.g., gas, electricity, etc. Amount of timber used in furniture, house building or other chores will be reduced with the substitution of wood composite materials, alternative reinforced building materials and the like ( [5] , [43] ). Another fact is that both the government and private sectors can induce several afforestation programs and make them successful if GDP/income per capita is above a certain level. The successful reforestation program in the Republic of Korea and the recent afforestation/reforestation success in Vietnam corroborate this statement ( [8] , [11] , [36] , [49] ). Furthermore, with increasing income per capita, education and awareness about the environment will also increase, which will in turn help reduce the rate of deforestation. However, all of these factors should be considered to contain uncertainties.

Shafik & Bandyopadhyay ( [67] ) first did an empirical study on deforestation in 1992. In 1976, Samuelson had hypothesized an EKC relationship with respect to forestry and conservation in a seminal paper on the economics of deforestation ( [7] ). However, Shafik & Bandyopadhyay ( [67] ) yielded no statistically significant evidence for EKC, which means there was a positive relationship between income per capita and deforestation. Tab. 1 shows the different EKC studies for deforestation mostly cited by Winslow ( [79] ). They studied data for 66 countries using a log linear model. Their study considered data produced between 1962 and 1986. Shafik ( [66] ) yielded the same result as Shafik & Bandyopadhyay ( [67] ) for deforestation using Quadratic, FE model. Bhattarai & Hammig ( [7] ) conducted a vast study of EKC for deforestation in 66 tropical countries. A quadratic RE model to estimate those aggregated data provided no statistically significant support for an inverted U-shape EKC. When they studied data (using cubic, FE and RE model) of 31 countries in Africa, they found a turning point from which deforestation decreases. This peak was at an income per capita of US$ 1300. However, there was another turning point from which deforestation began to increase again. This trough point was at an income per capita of US$ 5000. One experiment, however, was particularly revealing for EKC in relation to deforestation. A cubic FE and RE model for the data of 20 countries in Latin America has shown a turning point in deforestation at US$ 6600. Koop & Tole ( [40] ) studied the facts for Latin America in a Quadratic, FE model and found a turning point at an income per capita of US$ 8660.

Tab. 1 - EKC studies for deforestation. FE and RE means Fixed effect and Random Effect model, respectively.

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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.

  Economic growth and deforestation in Bangladesh 

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.

Macro-economy in Bangladesh

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).

Path of EKC for deforestation in Bangladesh

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.

CDM as a flexible mechanism

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.

REDD+ to slow down deforestation

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] ).

Legal and policy issues of reducing deforestation in Bangladesh

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.

  Conclusion 

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.

  Acknowledgement 

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.

  References

  authors’ info, authors’ affiliation, corresponding author,   paper info.

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

Paper history

Received: Aug 13, 2010 Accepted: Dec 13, 2010

First online: Jan 27, 2011 Publication Date: Jan 27, 2011 Publication Time: 1.50 months

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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.

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Article Contents

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.

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How Forests Attract Rain: An Examination of a New Hypothesis

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.

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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

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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.

Water yields.

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.

Vegetation feedbacks.

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.

Evolution and emergent stability.

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.

Paleoclimates.

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.

Managed vegetation.

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.

Greening deserts.

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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What Is Deforestation?

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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?

Causes of Deforestation

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.

At-a-glance: Deforestation Facts and Figures

• Africa and South America suffer the largest loss of forest worldwide.
• Tropical rainforests are home to more than half of all species on the planet.
• 73 percent of the world's forests are publicly owned.
• Only 18 percent of the world's forests are designated for conservation.

[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

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 ].

Urban Sprawl

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.

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 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

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.

Rain and Flooding

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 ].

Indigenous Communities

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 ].

What Happened at Easter Island?

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:

• Conservation International : Teaches local farmers how to maximize their existing land, rather than clear forested areas
• The World Wildlife Fund : Works to shape policies and teams with communities to preserve forested land
• Rainforest Action Network : Uses in-your-face advertising campaigns to call attention to the rainforests
• The Environmental Defense Fund : Champions government bills that provide financial incentive to private landowners (such as farmers) who practice land conservation
• The Sierra Club : Works to protect and restore U.S. forests
• Amazon Watch : Defends the rights of Indigenous people and communities faced with industrial development
• The Nature Conservancy : Has developed several initiatives to advance conservation

Reforestation Efforts

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:

• Eco-forestry : Only carefully selected trees are cut down and are transported with minimal damage to the area; the forest ecosystem is preserved while commercial timber extraction is still permitted.
• Green business : Focuses on recycled paper and wood products, wood alternatives and environmentally responsible consumerism
• Land use planning : Advocates environmentally friendly development techniques, such as reduction of urban and suburban sprawl
• Community forestry : Concerned citizens come together to manage and participate in keeping their local forests viable and sustainable

[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 ].

Deforestation FAQS

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.

• How Easter Island Works
• How Rainforests Work
• How the Sierra Club Works
• How the Rocky Mountain Institute Works
• How Floods Work
• How the Nature Conservancy Works
• "68% of the world population projected to live in urban areas by 2050, says UN." United Nations. May 16, 2018. (Oct. 15, 2023). https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html
• Associated Press. "Raw Video: Ford Waxes Chest for Charity." May 20, 2008. (Oct. 15, 2023). https://www.youtube.com/watch?v=bPiFCIs3_mI
• BBC. "Brazil Amazon deforestation soars." Jan. 24, 2008. (May 20, 2008) http://news.bbc.co.uk/2/hi/americas/7206165.stm
• BBC. "Deforestation and the Greenhouse Effect." March 4, 2008. (May 27, 2008) http://www.bbc.co.uk/dna/h2g2/A3556848
• Bentz, B.; Klepzig, K. (January 2014). Bark Beetles and Climate Change in the United States. U.S. Department of Agriculture, Forest Service, Climate Change Resource Center. www.fs.usda.gov/ccrc/topics/insect-disturbance/bark-beetles
• Butler, Rhett A. "An interview with ethnobotanist Dr. Mark Plotkin." Mongabay.com. Oct 31, 2006. (May 27, 2008) https://www.butlernature.com/2022/01/31/interview-with-ethnobotanist-mark-plotkin/
• Butler, Rhett A. "Logging." Tropical Rainforests: Imperiled Riches - Threatened Rainforests. Jan 9, 2006. Mongabay.com. (May 20, 2008) http://rainforests.mongabay.com/0807.htm
• Carbonfund.org. "Reforestation." 2008. (May 28, 2008) http://www.carbonfund.org/
• Colitt, Raymond. "Brazil Indians, activists protest over Amazon dam." Reuters. May 21, 2008. (May 20, 2008) http://www.reuters.com/article/americasCrisis/idUSN21415214
• Conservation International. "Forest Conservation Facts." (Oct. 15, 2023) https://www.conservation.org/stories/forest-conservation-facts
• Dangerfield, Whitney. "The Mystery of Easter Island." Smithsonian.com. April 1, 2007. (May 28, 2008) http://www.smithsonianmag.com/people-places/The_Mystery_of_Easter_Island.html?c=y&page=1
• Food and Agriculture Organization of the United Nations. "Global Forest Resources Assessment 2020." Nov. 18, 2020. (Oct. 15, 2023). https://www.fao.org/documents/card/en/c/ca9825en
• Food and Agriculture Organization of the United Nations. "Intact mangroves could have reduced Nargis damage." May 15, 2008. (May 27, 2008) https://www.fao.org/asiapacific/news/detail-events/en/c/46053/
• Forest Protection Portal. "Ecological Science Based Forest Preservation & Conservation Advocacy." 2008. (May 28, 2008) https://forests.org/
• Giljum, S., Maus, V., Kuschnig, N., Luckeneder, S., Tost, M., Sonter, L. J., & Bebbington, A. J. (2022). A pantropical assessment of deforestation caused by industrial mining. Proceedings of the National Academy of Sciences, 119(38), e2118273119. https://doi.org/10.1073/pnas.2118273119
• Kristof, Nicholas D. "Can We Be as Smart as Bats?" New York Times. May 1, 2008. (May 27, 2008) http://www.nytimes.com/2008/05/01/opinion/01kristof.html
• Lindsey, Rebecca. "Tropical Deforestation." NASA. March 30, 2007. (May 27, 2008) http://earthobservatory.nasa.gov/Library/Deforestation/
• "Palm Oil." World Wildlife Fund. (Oct. 15, 2023). https://www.worldwildlife.org/industries/palm-oil
• Pomeranz, Ken and Wong, Bin. "China and Europe: 1780-1937." Columbia University. 2004. (May 27, 2008) http://afe.easia.columbia.edu/chinawh/web/s6/s6_2.html
• Science Daily. "Tropical Reforestation Aided By Bats." April 28, 2008. (May 28, 2008) http://www.sciencedaily.com/releases/2008/04/080428124235.htm
• USA Today. "Haiti Floods Due to Deforestation." Sept. 23, 2004. (Oct. 15, 2023). https://www.cbsnews.com/news/haiti-floods-due-to-deforestation/
• World Wildlife Federation. "Tropical Rainforests." (Oct. 15, 2023). https://wwf.panda.org/discover/our_focus/forests_practice/importance_forests/tropical_rainforest/

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May 30, 2020

Rethinking Easter Island’s Historic ‘Collapse’

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.

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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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Revisiting the deforestation-induced EKC hypothesis: the role of democracy in Bangladesh

• Published: 13 June 2020
• Volume 87 , pages 53–74, ( 2022 )

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• Muntasir Murshed   ORCID: orcid.org/0000-0001-9872-8742 1  

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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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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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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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