Economic Issues Related to Asian Deforestation

2021 ◽  
Author(s):  
Stefanie Onder ◽  
James T. Erbaugh ◽  
Georgia Christina Kosmidou-Bradley
Keyword(s):  
Supply Chains ◽  
Multinational Corporations ◽  
Forest Cover ◽  
Local Population ◽  
Economic Incentives ◽  
Forest Monitoring ◽  
Tree Cover ◽  
Forest Governance ◽  
Observation Data ◽  
The Impact

The loss of Asian forests represents one of the most significant changes in contemporary land cover. Between 2000 and 2020 alone, an area twice the size of Malaysia has lost its tree cover as measured by Earth observation data. These trends have significant repercussions for greenhouse gas emissions, carbon storage, the conservation of biodiversity, and the wellbeing of Indigenous Peoples and local communities (IPLCs), making Asian deforestation a phenomenon of global concern. There are many immediate factors that drive deforestation across Asia, but the conversion to commodity agriculture is the leading cause. Most notably, the expansion of oil palm and rubber plantations by both multinational corporations and smallholders has led to dramatic conversion of forests. The production of timber as well as pulp and paper has further contributed to significant deforestation, with the evolution of each sector often driven by government policies, such as logging bans. However, it is the underlying drivers (i.e., distal and proximate causes) that determine where and when commodity production displaces forest cover. They are particularly challenging to tackle in a globalized world, where consumption patterns driven by local population and income growth lead to environmental and social change in distant producer countries, including in Asia. Certification programs and legality requirements have been put in place to address these externalities with varying success. Deforestation in Asia is also facilitated by weak governance and regulatory frameworks, where forest rights are often unclear, and financial, technological, and human resources for forest monitoring are limited. Several contemporary forest governance strategies seek to promote sustainable management of Asian forests. Financial mechanisms such as reducing emissions from deforestation and forest degradation (REDD+) and payments for ecosystem services (PES) schemes seek to provide economic incentives for forest conservation. Pledges and activities to remove deforestation from commodity supply chains seek to respond to consumer demand, promote corporate environmental and social responsibility, and reduce the extent to which commodity supply chains contribute to Asian deforestation. And multiple state-led initiatives across Asia to empower IPLCs aim to align forest management objectives between national governments, subnational administrations, and local people. Assessing the impact of interventions related to financial mechanisms, corporate responsibility, and local forest governance will be critical to shaping the future of Asian forest cover change.

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

scholarly journals India’s Commitments to Increase Tree and Forest Cover: Consequences for Water Supply and Agriculture Production within the Central Indian Highlands

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 959
Author(s):  
Benjamin Clark ◽  
Ruth DeFries ◽  
Jagdish Krishnaswamy
Keyword(s):  
Groundwater Recharge ◽  
Forest Cover ◽  
Hydrological Modeling ◽  
Monsoon Season ◽  
Forest Policy ◽  
Central India ◽  
Field Measurements ◽  
Tree Cover ◽  
Policy Goals ◽  
The Impact

As part of its nationally determined contributions as well as national forest policy goals, India plans to boost tree cover to 33% of its land area. Land currently under other uses will require tree-plantations or reforestation to achieve this goal. This paper examines the effects of converting cropland to tree or forest cover in the Central India Highlands (CIH). The paper examines the impact of increased forest cover on groundwater infiltration and recharge, which are essential for sustainable Rabi (winter, non-monsoon) season irrigation and agricultural production. Field measurements of saturated hydraulic conductivity (Kfs) linked to hydrological modeling estimate increased forest cover impact on the CIH hydrology. Kfs tests in 118 sites demonstrate a significant land cover effect, with forest cover having a higher Kfs of 20.2 mm hr−1 than croplands (6.7mm hr−1). The spatial processes in hydrology (SPHY) model simulated forest cover from 2% to 75% and showed that each basin reacts differently, depending on the amount of agriculture under paddy. Paddy agriculture can compensate for low infiltration through increased depression storage, allowing for continuous infiltration and groundwater recharge. Expanding forest cover to 33% in the CIH would reduce groundwater recharge by 7.94 mm (−1%) when converting the average cropland and increase it by 15.38 mm (3%) if reforestation is conducted on non-paddy agriculture. Intermediate forest cover shows however shows potential for increase in net benefits.

scholarly journals Effect of oil palm sustainability certification on deforestation and fire in Indonesia

2017 ◽  
Vol 115 (1) ◽  
pp. 121-126 ◽  
Author(s):  
Kimberly M. Carlson ◽  
Robert Heilmayr ◽  
Holly K. Gibbs ◽  
Praveen Noojipady ◽  
David N. Burns ◽  
...  
Keyword(s):  
Palm Oil ◽  
Oil Palm ◽  
Forest Cover ◽  
Fire Detection ◽  
Tree Cover ◽  
Forest Loss ◽  
Detection Rates ◽  
Active Fire ◽  
Routine Monitoring ◽  
The Impact

Many major corporations and countries have made commitments to purchase or produce only “sustainable” palm oil, a commodity responsible for substantial tropical forest loss. Sustainability certification is the tool most used to fulfill these procurement policies, and around 20% of global palm oil production was certified by the Roundtable on Sustainable Palm Oil (RSPO) in 2017. However, the effect of certification on deforestation in oil palm plantations remains unclear. Here, we use a comprehensive dataset of RSPO-certified and noncertified oil palm plantations (∼188,000 km2) in Indonesia, the leading producer of palm oil, as well as annual remotely sensed metrics of tree cover loss and fire occurrence, to evaluate the impact of certification on deforestation and fire from 2001 to 2015. While forest loss and fire continued after RSPO certification, certified palm oil was associated with reduced deforestation. Certification lowered deforestation by 33% from a counterfactual of 9.8 to 6.6% y−1. Nevertheless, most plantations contained little residual forest when they received certification. As a result, by 2015, certified areas held less than 1% of forests remaining within Indonesian oil palm plantations. Moreover, certification had no causal impact on forest loss in peatlands or active fire detection rates. Broader adoption of certification in forested regions, strict requirements to avoid all peat, and routine monitoring of clearly defined forest cover loss in certified and RSPO member-held plantations appear necessary if the RSPO is to yield conservation and climate benefits from reductions in tropical deforestation.

Forest Management, Farmers' Practices and Biodiversity Conservation in the Monogaga Protected Coastal Forest in Southwest Côte D'ivoire

Africa ◽  
2007 ◽  
Vol 77 (1) ◽  
pp. 63-85 ◽  
Author(s):  
C. Y. Adou Yao ◽  
Barnard Roussel
Keyword(s):  
Management Practices ◽  
Forest Cover ◽  
Local Population ◽  
Agricultural Practices ◽  
Iucn Red List ◽  
Coastal Forest ◽  
Species List ◽  
Conservation Area ◽  
The Government ◽  
The Impact

AbstractThe emergence of biodiversity standards in the nature conservation literature requires that we consider the interactions between conservation and local practices from a new angle. The coastal forest of Monogaga, a protected area inhabited by a local population, is an ideal terrain for comparing the impact of local agricultural practices and the activities of Sodefor, the government agency charged with the management of this conservation area. The discourses and uses of forest resources of these two actors allow us to compare the biodiversity of forest cover categories recognized by peasant farmers and Sodefor, using the standard statistical methods for measuring biodiversity (the Shannon and Weaver index, species richness, number of special status species).For Sodefor, it is the most dense forest ecosystems (the ‘black forests’ ) and the lands that they occupy that constitute the area's natural heritage. The agency believes that these forests must be protected from all human uses, especially farming, if the forest is to be transmitted to future generations. In contrast, Wanne farmers view the old forests (kporo) as long-term fallows (teteklwoa) or reserves of fertile land that will be cleared when there is a need for more farmland in the future. For them, patrimony is constituted by the intergenerational transmission of a bundle of resource access and farming rights within lineages.With regard to biodiversity, a comparison of the two types of resource management practices (Sodefor and farmer) gives nuanced results. The farmers' areas are more diverse than those of Sodefor when considering the Aké Assi threatened species list. For the Sassandrian species list, both management types maintained the same quantity of species. For endemics and the IUCN red list species, the spatial units controlled by Sodefor show more diversity.

scholarly journals Missing the Target: Brazil's Agricultural Policy Indirectly Subsidizes Foreign Investments to the Detriment of Smallholder Farmers and Local Agribusiness

2022 ◽  
Vol 5 ◽  
Author(s):  
Graciella Corcioli ◽  
Gabriel da Silva Medina ◽  
Cristiano Alencar Arrais
Keyword(s):  
Supply Chains ◽  
Multinational Corporations ◽  
Agricultural Policy ◽  
Agricultural Sector ◽  
Smallholder Farmers ◽  
Direct Foreign Investment ◽  
Foreign Companies ◽  
Family Farmers ◽  
Transnational Companies ◽  
The Impact

Currently there is controversy about the effect of direct foreign investment in the Brazilian agricultural sector, mainly due to the impact it has on small farmers, land use, the environment, and food security. In this context, Brazil finds itself in an even more delicate situation, since in order to remain a bulwark of the economy, Brazilian agribusiness depends heavily on public policies that directly impact its treasury. This suggests there is an indirect transfer of public resources to transnational companies involved in agribusiness production chains. This paper assesses the allocation of agricultural credits in Brazil and the market share held by Brazilian groups, vis-à-vis multinational corporations in the agribusiness supply chains. The study was carried out analyzing the three largest supply chains established in the country: soybean, corn, and cattle. Results reveal that 75% of the operating credit (crédito de custeio), which represents 60% of the total government credit in Brazil, goes directly to soybean, corn, and cattle farmers. Most of this subsidized credit budget goes to the soybean farmers, which are mostly encompassed by large farmers. Results also reveal that 76.1% of the soybean supply chain in Brazil is controlled by foreign multinational corporations. These findings suggest that resources invested in large farmers that take part in supply chains controlled by multinational foreign groups end up indirectly financing foreign companies to the detriment of local smallholder farmers and domestic agribusiness. This highlights the need for restructuring Brazilian agricultural policy in favor of family farmers and domestic agribusiness.

scholarly journals China's fight to halt tree cover loss

2017 ◽  
Vol 284 (1854) ◽  
pp. 20162559 ◽  
Author(s):  
Antje Ahrends ◽  
Peter M. Hollingsworth ◽  
Philip Beckschäfer ◽  
Huafang Chen ◽  
Robert J. Zomer ◽  
...  
Keyword(s):  
Forest Cover ◽  
Forest Tree ◽  
Forest Monitoring ◽  
Tree Cover ◽  
Environmental Modelling ◽  
The Past ◽  
Environmental Suitability ◽  
Crown Cover ◽  
Order Of Magnitude ◽  
Definition Of

China is investing immense resources for planting trees, totalling more than US$ 100 billion in the past decade alone. Every year, China reports more afforestation than the rest of the world combined. Here, we show that China's forest cover gains are highly definition-dependent. If the definition of ‘forest’ follows FAO criteria (including immature and temporarily unstocked areas), China has gained 434 000 km 2 between 2000 and 2010. However, remotely detectable gains of vegetation that non-specialists would view as forest (tree cover higher than 5 m and minimum 50% crown cover) are an order of magnitude less (33 000 km 2 ). Using high-resolution maps and environmental modelling, we estimate that approximately 50% of the world's forest with minimum 50% crown cover has been lost in the past approximately 10 000 years. China historically lost 1.9–2.7 million km 2 (59–67%), and substantial losses continue. At the same time, most of China's afforestation investment targets environments that our model classes as unsuitable for trees. Here, gains detectable via satellite imagery are limited. Conversely, the regions where modest gains are detected are environmentally suitable but have received little afforestation investment due to conflicting land-use demands for agriculture and urbanization. This highlights the need for refined forest monitoring, and greater consideration of environmental suitability in afforestation programmes.

scholarly journals Evidence that a national REDD+ program reduces tree cover loss and carbon emissions in a high forest cover, low deforestation country

2019 ◽  
Vol 116 (49) ◽  
pp. 24492-24499 ◽  
Author(s):  
Anand Roopsind ◽  
Brent Sohngen ◽  
Jodi Brandt
Keyword(s):  
Forest Cover ◽  
Forest Degradation ◽  
Tree Cover ◽  
Forest Protection ◽  
Forest Policies ◽  
Deforestation Rates ◽  
Climate Change Mitigation Policy ◽  
Implementation Period ◽  
Rich Countries ◽  
The Impact

Reducing emissions from deforestation and forest degradation (REDD+) is a climate change mitigation policy in which rich countries provide payments to developing countries for protecting their forests. In 2009, the countries of Norway and Guyana entered into one of the first bilateral REDD+ programs, with Norway offering to pay US$250 million to Guyana if annual deforestation rates remained below 0.056% from 2010 to 2015. To quantify the impact of this national REDD+ program, we construct a counterfactual times-series trajectory of annual tree cover loss using synthetic matching. This analytical approach allows us to quantify tree cover loss that would have occurred in the absence of the Norway-Guyana REDD+ program. We found that the Norway-Guyana REDD+ program reduced tree cover loss by 35% during the implementation period (2010 to 2015), equivalent to 12.8 million tons of avoided CO2 emissions. Our analysis indicates that national REDD+ payments attenuated the effect of increases in gold prices, an internationally traded commodity that is the primary deforestation driver in Guyana. Overall, we found strong evidence that the program met the additionality criteria of REDD+. However, we found that tree cover loss increased after the payments ended, and therefore, our results suggest that without continued payments, forest protection is not guaranteed. On the issue of leakage, which is complex and difficult to quantify, a multinational REDD+ program for a region could address leakage that results from differences in forest policies between neighboring countries.

scholarly journals Identifying Biases in Global Tree Cover Products: A Case Study in Costa Rica

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 853 ◽  
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Land Cover ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Monitoring ◽  
Tree Cover ◽  
Agricultural Fields ◽  
Tropical Country ◽  
Row Crops ◽  
Regional Forest

Global tree cover products are widely used in analyses of deforestation, fragmentation, and connectivity, but are rarely critically assessed. Inaccuracies in these products could have consequences for future decision making, especially in data-poor regions like the tropics. In this study, potential biases in global and regional tree cover products were assessed across a diverse tropical country, Costa Rica. Two global tree cover products and one regional national forest cover map were evaluated along biophysical gradients in elevation, precipitation, and agricultural land cover. To quantify product accuracy and bias, freely available high-resolution imagery was used to validate tree and land cover across these gradients. Although the regional forest cover map was comparable in accuracy to a widely-used global forest map (the Global Forest Change of Hansen et al., also known as the GFC), another global forest map (derived from a cropland dataset) had the highest accuracy. Both global and regional forest cover products showed small to severe biases along biophysical gradients. Unlike the regional map, the global GFC map strongly underestimated tree cover (>10% difference) below 189 mm of precipitation and at elevations above 2000 m, with a larger bias for precipitation. All map products misclassified agricultural fields as forest, but the GFC product particularly misclassified row crops and perennial erect crops (banana, oil palm, and coffee), with maximum tree cover in agricultural fields of 89%–100% across all crops. Our analysis calls into further question the utility of the GFC product for global forest monitoring outside humid regions, indicating that, in tropical regions, the GFC product is most accurate in areas with high, aseasonal rainfall, low relief, and low cropland area. Given that forest product errors are spatially distributed along biophysical gradients, researchers should account for these spatial biases when attempting to analyze or generate forest map products.

scholarly journals Potential improvement for forest cover and forest degradation mapping with the forthcoming Sentinel-2 program

2015 ◽  
Vol XL-7/W3 ◽  
pp. 417-423 ◽  
Author(s):  
L. Hojas-Gascon ◽  
A. Belward ◽  
H. Eva ◽  
G. Ceccherini ◽  
O. Hagolle ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Forest Canopy ◽  
Forest Cover ◽  
Spectral Characteristics ◽  
Canopy Cover ◽  
Tree Cover ◽  
Optical Data ◽  
Validation Data ◽  
The Impact ◽  
Sentinel 2

The forthcoming European Space Agency’s Sentinel-2 mission promises to provide high (10 m) resolution optical data at higher temporal frequencies (5 day revisit with two operational satellites) than previously available. CNES, the French national space agency, launched a program in 2013, ‘SPOT4 take 5’, to simulate such a dataflow using the SPOT HRV sensor, which has similar spectral characteristics to the Sentinel sensor, but lower (20m) spatial resolution. Such data flow enables the analysis of the satellite images using temporal analysis, an approach previously restricted to lower spatial resolution sensors. We acquired 23 such images over Tanzania for the period from February to June 2013. The data were analysed with aim of discriminating between different forest cover percentages for landscape units of 0.5 ha over a site characterised by deciduous intact and degraded forests. The SPOT data were processed by one extracting temporal vegetation indices. We assessed the impact of the high acquisition rate with respect to the current rate of one image every 16 days. Validation data, giving the percentage of forest canopy cover in each land unit were provided by very high resolution satellite data. Results show that using the full temporal series it is possible to discriminate between forest units with differences of more than 40% tree cover or more. Classification errors fell exclusively into the adjacent forest canopy cover class of 20% or less. The analyses show that forestation mapping and degradation monitoring will be substantially improved with the Sentinel-2 program.

scholarly journals Assessing MODIS Vegetation Continuous Fields tree cover product (collection 6): performance and applicability in tropical forests and savannas

2021 ◽  
Author(s):  
Rahayu Adzhar ◽  
Douglas I. Kelley ◽  
Ning Dong ◽  
Mireia Torello Raventos ◽  
Elmar Veenendaal ◽  
...  
Keyword(s):  
Field Data ◽  
Forest Cover ◽  
Tree Cover ◽  
Tropical Savannas ◽  
Moderate Resolution ◽  
Forest Cover Changes ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Continuous Fields ◽  
The Impact

Abstract. The Moderate Resolution Imaging Spectroradiometer vegetation continuous fields (MODIS VCF) Earth observation product is widely used to estimate forest cover changes, parameterise vegetation and Earth System models, and as a reference for validation or calibration where field data is limited. However, although limited independent validations of MODIS VCF have shown that MODIS VCF's accuracy decreases when estimating tree cover in sparsely-vegetated areas, such as in tropical savannas, no study has yet assessed the impact this may have on the VCF based tree cover distributions used by many in their research. Using tropical forest and savanna inventory data collected by the TROpical Biomes In Transition (TROBIT) project, we produce a series of corrections that take into account (i) the spatial disparity between the in-situ plot size and the MODIS VCF pixel, and (ii) the trees' spatial distribution within in-situ plots. We then applied our corrections to areas identified as forest or savanna in the International Geosphere-Biosphere Programme (IGBP) land cover mapping product. All IGBP classes identified as savanna show substantial increases in cover after correction, indicating that the most recent version of MODIS VCF consistently underestimates woody cover in tropical savannas. We estimate that MODIS VCF could be underestimating tropical tree cover by between 9–15 %. Models that use VCF as their benchmark could be underestimating the carbon uptake in forest-savanna areas and misrepresenting forest-savanna dynamics. While more detailed in-situ field data is necessary to produce more accurate and reliable corrections, we recommend caution when using MODIS VCF in tropical savannas.

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