Has global deforestation accelerated due to the COVID-19 pandemic?

As the COVID-19 pandemic unfolded,questions arose as to whether the pandemic would amplify or pacify tropical deforestation.Early reports warned of increased deforestation rates;however,these studies were limited to a few months in 2020 or to selected regions.To better understand how the pandemic infl uenced tropical deforestation globally,this study used historical deforestation data(2004–2019)from the Terra-i pantropical land cover change monitoring system to project expected deforestation trends for 2020,which were used to determine whether observed deforestation deviated from expected trajectories after the fi rst COVID-19 cases were reported.Time series analyses were conducted at the regional level for the Americas,Africa and Asia and at the country level for Brazil,Colombia,Peru,the Democratic Republic of Congo and Indonesia.Our results suggest that the pandemic did not alter the course of deforestation trends in some countries(e.g.,Brazil,Indonesia),while it did in others(e.g.,Peru).We posit the importance of monitoring the long-term eff ects of the pandemic on deforestation trends as countries prioritize economic recovery in the aftermath of the pandemic.

Impact of forest governance and enforcement on deforestation and forest degradation at the district level:A study in West Bengal State,India

According to the United Nations Environmental Programme(UNEP),the world loses 1.0×106hm2forest land through deforestation annually.About 1.6×106people who depend on forests for livelihood are negatively affected by deforestation and forest degradation.The paper attempts to study the impact of forest governance,enforcement and socio-economic factors on deforestation and forest degradation at the local level in West Bengal State,India.The study was based on questionnaire survey data during 2020–2021 collected from three western districts(Purulia,Bankura,and Paschim Medinipur)where deforestation and poverty rates are higher than other districts in West Bengal State.The total number of selected villages was 29,and the total sample households were 693.A stratified random sampling technique was used to collect data,and a questionnaire was followed.Forest governance and enforcement indices were constructed using United Nation Development Programme(UNDP)methodology and a step-wise logistic regression model was used to identify the factors affecting deforestation and forest degradation.The result of this study showed that four factors(illegal logging,weak forest administration,encroachment,and poverty)are identified for the causes of deforestation and forest degradation.It is observed that six indices of forest governance(rule of law,transparency,accountability,participation,inclusiveness and equitability,and efficiency and effectiveness)are relatively high in Purulia District.Moreover,this study shows that Purulia and Bankura districts follow medium forest governance,while Paschim Medinipur District has poor forest governance.The enforcement index is found to be highest in Purulia District(0.717)and lowest for Paschim Medinipur District(0.257).Finally,weak forest governance,poor socio-economic conditions of the households,and weak enforcement lead to the deforestation and forest degradation in the study area.Therefore,governments should strengthen law enforcement and encourage sustainable forest certification schemes to combat illegal logging.

Anthropogenic Climate Change, Deforestation and Renewable Energy

Since the Industrial Revolution, greenhouse gas (GHG) emission, especially global CO2 emission (GCE) has greatly increased with the growth of global human population (GHP), which has caused climate change. Both GCE and GHP are positively related with the rise of global mean surface temperature (GMST). Our empirical research shows that the impact from GCE on GMST is 7.72 times of that from TSI, and the impact from GHP on GMST is 7.9 times of that from TSI. The growth rate of global surface temperature was slower from 1998 to 2012, which was mainly caused by the decadal cooling of the tropical Pacific Ocean-La Niña. Deforestation and vegetation degradation affect climate change, feedback radiation between the atmosphere and the biosphere account for 30% of the variation in global surface radiation and precipitation. The share of renewable energy remains small in primary energy consumption due to their disadvantages.

Effects of Accelerated Soil Erosion on Soil Nutrient Loss After Deforestation on the Loess Plateau

Soil erosion and nutrient losses on newly-deforested lands in the Ziwuling Region on the Loess Plateau of China were monitored to quantitatively evaluate the effects of accelerated soil erosion, caused by deforestation, on organic matter, nitrogen and phosphorus losses. Eight natural runoff plots were established on the loessial hill slopes representing different erosion patterns of dominant erosion processes including sheet, rill and shallow gully (similar to ephemeral gully). Sediment samples were collected after each erosive rainfall event. Results showed that soil nutrients losses increased with an increase of erosion intensity. Linear relations between the losses of organic matter, total N, NH4-N, and available P and erosion intensity were found. Nutrient content per unit amount of eroded sediment decreased from the sheet to the shallow gully erosion zones, whereas total nutrient loss increased. Compared with topsoil, nutrients in eroded sediment were enriched, especially available P and NH4-N. The intensity of soil nutrient losses was also closely related to soil erosion intensity and pattern with the most severe soil erosion and nutrient loss occurring in the shallow gully channels on loessial hill slopes. These research findings will help to improve the understanding of the relation between accelerated erosion process after deforestation and soil quality degradation and to design better eco-environmental rehabilitation schemes for the Loess Plateau.

Numerical Simulation for the Impact of Deforestation on Climate in China and Its Neighboring Regions

In this paper, the CCMOB model is used to study the effect of the deforestation on the climate of China and its neighboring regions. On the assumption that the forest in China would be replaced by the vegetation(such as grassland), the distribution of the albedo changed was calculated. The initial fields used were taken from the FGGE zonal mean data on 16 July, 1979. In the control simulation, the observed albedo data were used to modify the physical parameters of the original model. The control and sensitive experiments were run each for 210 days, in which the external forcing fields were fixed in July. As a result, we find that the East Asian Monsoon, Hadley cell and troposphere easterly jet are weakened for the deforestation in China. The precipitation and cloud amount over China are also decreased. The changes in evaporation and surface temperature are small. The results also show that the deforestation in China exerts a remarkable effect on the climate in the neighboring regions of China.

Multi-temporal forest cover dynamics in Kashmir Himalayan region for assessing deforestation and forest degradation in the context of REDD+ policy

The role of forests is being actively considered under the agenda of REDD＋ （Reducing Emissions from Deforestation and Forest Degradation plus） aimed at reducing emissions related to changes in forest cover and forest quality. Forests in general have undergone negative changes in the past in the form of deforestation and degradation, while in some countries positive changes are reported in the form of conservation, sustainable management of forests and enhancement of carbon stock. The present study in the Kashmir Himalayan forests is an effort to assess historical forest cover changes that took place from 1980 to 2009 and to predict the same for 2030 on the basis of past trend using geospatial modeling approach. Landsat data （Multispectral Scanner （MSS）, Thematic Mapper （TM） and Enhanced Thematic Mapper （ETM＋）） was used for the years 1980, 199o and （2001, 2009） respectively and change detection analysis between the dates was performed. The maps generated were validated through ground truthing. The study area （3375.62 km^2） from 1980-2009 has uffered deforestation and forest degradation of about 126 km^2 and 239.02 km^2 respectively which can be claimed under negative options of REDD＋, while as the area that experienced no change （1514 km^2） can be claimed under conservation. A small area （23.31 km^2） observed as positive change can be claimed under positive options. The projected estimates of forest cover for 2030 showed increased deforestation and forest degradation on the basis of trend analysis using Cellular Automata （CA） Markov modeling. Despite the fact that country as a whole has registered a net positive change in the past few decades, but there are regions like Kashmir region of western Himalaya which have constantly undergoing deforestation as well as degradation in the past few decades.

Assessment of causes and future deforestation in the mountainous tropical forest of Timor Island, Indonesia

The Mutis-Timau Forest Complex,one of the remaining mountainous tropical forest areas in Timor Island,eastern Indonesia that covers an area of 31,984 ha,tends to decrease gradually.Efforts to secure mountain forest functions and counteract the negative impact of declining forest areas are often constrained by data uncertainty on factors contributing to deforestation.For this reason,this study attempts to develop models of deforestation and predict future deforestation in the Mutis-Timau Forest Complex.We constructed models of deforestation that describe the relationship between deforestation and factors contributing to deforestation using spatial statistical models.In this model,we used the deforestation data for the 1987-2017 period obtained from a previous study as dependent variables and the potential causes of deforestation generated from Geographic Information System spatial analysis as independent variables.Using the probability of deforestation derived from the model,we predicted future deforestation under two different scenarios,namely,business-as-usual(as the reference scenario)and reducing emission fromdeforestation and forest degradation.Our findings showed that a positive relationship exists between probability of deforestation,distance to the settlement,and population density variables,whereas a negative relationship exists between likelihood of deforestation,elevation,slope,distance to the road,distance to the savanna,and forest management unit variables.During the 2017-2030 period,under the business-as-usual scenario,the Mutis-Timau Forest Complex will lose 1327.65 ha in forest area with an annual deforestation rate of 0.54%.Meanwhile,under the reducing emission from deforestation and forest degradation scenario,the overall forest loss was estimated to be 1237.11 ha with an annual deforestation rate of 0.50%.The predicted area of avoided deforestation in 2017-2030 under the reducing emission from deforestation and forest degradation scenario was 90.54 ha.Such data and information are important for the Mutis-Timau Forest Complex authority in prioritizing actions for combating deforestation and designing appropriate forest-related policies and supporting data for reducing emission from deforestation and forest degradation programme or other incentive schemes in reducing deforestation.

Socio-Economic Drivers of Deforestation in Roghani Valley,Hindu-Raj Mountains,Northern Pakistan

Deforestation and associated ecological disturbances are the issues of global concern.Researchers have investigated a number of driving forces which accelerate the rate of deforestation at local and regional levels.These include poverty,population growth,market demand and prices,political instability,agricultural expansion and changes in property right and ownership regimes.This paper seeks to explore the impacts of population growth,changing tenure system and other socioeconomic factors on the forest cover of Roghani Valley,located in Hindu Raj Mountains,Northern Pakistan.The present study is mainly based on information collected through participatory observation,selfadministered interviews and questionnaire survey.Geographical Information System(GIS) database is also used for mapping and quantification.The results reveal that in the past three to four decades the study area has been subjected to severe deforestation and about half of the forest area has been converted into barren land.Thus,the area under natural forests decreased from 2099 to 1444 hectares in four decades.This large-scale deforestation is attributed to both proximate and under lying causes particularly traditional land tenure system and demographic development.Consequently,forest resources have been degraded and a number of plant species have disappeared from the forests of the study area while several others are in the process of disappearance.

Impact of Climate Change and Deforestation on Stream Discharge and Sediment Yield in Phu Luong Watershed, Viet Nam

The purpose of this paper is to apply ＂Soil and Water Assessment Tool （SWAT）＂ model to assess the impacts of climate change and deforestation on stream discharge and sediment yield from Phu Luong watershed in Northern Viet Nam. Among the three climate change scenarios B 1, B2, and A2, representing low, medium, and high levels of greenhouse gas emission, respectively were set up for Viet Nam, the B2 scenario was selected for this study. Two land use scenarios （S1-2030 and $2-2050） were formulated combination with climate change in WSAT simulation. In B2 climate change scenario, mean temperature increases 0.7℃（2030） and 1.3 ℃ （2050）; annual rainfall increases 2.1% （2030） and 3.80% （2050） respect to baseline scenario. The results show that the stream discharge is likely to increase in the future during the wet season with increasing threats of sedimentation.

The Extent and Drivers of Deforestation and Forest Degradation in Masito-Ugalla Ecosystem, Kigoma Region, Tanzania

Deforestation and forest degradation has been observed to be rampant in Masito-Ugalla ecosystem, Kigoma Region, western part of Tanzania. This paper therefore, intended to assess the extent of deforestation and forest degradation in the area, and to determine their causes. A total of 101 respondents were considered as the sample size for this study. The methods used for data collection were household questionnaire interviews, in-depth interviews, focus group discussions, analysis of satellite images and direct observation. The findings indicated that deforestation was occurring in the study area. Satellite data revealed diminished closed woodland, bushed grassland, forest and thickets between 1990 and 2014. On the contrary, settlement area, cultivated land and open woodland had increased during the same time frame. Proximate factors causing deforestation and forest degradation included agricultural expansion, wood extraction and expansion of settlement area. Underlying factors included population growth, poverty, poor levels of education, lack of employment, corruption and embezzlement of public funds by politicians and senior government officials;and high demand for fuel-wood. Biophysical drivers like incidences of unplanned wildfires and socio trigger events notably civil strife were also important. In order to minimize the problem and based on the factors augmenting deforestation and forest degradation in the Masito-Ugalla ecosystem and their coupled negative consequences, effective environmental conservation education, increased patrols, effective law enforcement and provision of alternative energy sources are necessary.

Assessment of Drivers of Deforestation and Forest Degradation in Phnom Tbeng Forest Based on Socio-Economic Surveys

Carbon emission reductions through reducing deforestation and forest degradation or REDD+ scheme of the United Nations Framework Convention on Climate Change could not be achieved without understanding the drivers of deforestation and forest degradation. Until recently, only a handful of study has focused on such drivers. Cambodia experienced rapid deforestation and forest degradation despite growing international interests in protecting forests for carbon revenue generation. This paper was designed to assess livelihood of forest-dependent community and drivers of deforestation and forest degradation in Cambodia. Quantitative and qualitative methods were used to collect socio-economic data from 42 households living in Phnom Tbeng forest, where annual deforestation rate was about 2.4% between 2004 and 2009. Our results suggest that local people depend on forests for income generation, subsistence use and social identity. About 90% of the respondents believed that deforestation was resulted from illegal logging, slush and burn agricultural practices, land clearing for large plantation, land encroachment, firewood extraction, charcoal production and forest fire. As the population has increased rapidly and almost 100% of local people depend on fuelwood for cooking, fuelwood collection will continue to cause deforestation and forest degradation unless alternative sources of affordable energy are provided. Appropriate policy interventions should be proposed to reduce the drivers obtained in this study because if drivers cannot be reduced, it is not possible to reduce deforestation and forest degradation, and related carbon emissions.

Estimating the opportunity costs of avoiding oil palm-based deforestation in Indonesia:Implications for REDD

Reducing emissions due to deforestation is considered a low-cost option for mitigating climate change.However,the recent literature suggests higher opportunity costs because of specific deforestation drivers,which render reducing emissions from deforestation and forest degradation(REDD+)for mitigating climate change an uncertain,less attractive,and controversial option.Indonesia is one of the largest greenhouse gas emitters.Since 1989,53.80%of its oil palm expansion has come from forestlands,which has generated a significant amount of carbon emissions.This study uses official data and results from the relevant literature to estimate the costs of oil palm-based deforestation under various scenario assumptions,including different output prices,yields,time horizons,and discount rates.We also calculate the additional cost to preserve a 1-ha forest.We demonstrate that the average opportunity cost from avoiding oil palm-based deforestation is 24.42 USD/tCO_(2)eq in Indonesia,approximately 1.3 times the 2011 EUA carbon price.Additional sums of around 5,466.90–11,042.96 USD/ha should be provided to landowners for the deforestation avoidance caused by oil palm expansion.Special attention should be given to the extensive oil palm expansion in Indonesia and the resulting high opportunity costs for achieving the REDD+​target.

Spatial modelling of deforestation in Romanian Carpathian Mountains using GIS and Logistic Regression

Deforestation process represents a wide concern mainly in the mountain environments due to its role in global warming, biodiversity loss, land degradation and natural hazards occurrence. Thus, the present study is focused on the largest afforested landform unit of Romania and, consequently, the most affected area by forest losses: Carpathian Mountains. The main goal of the paper is to examine and analyze the various explanatory variables associated with deforestation process and to model the probability of deforestation using GIS spatial analysis and logistic regression. The forest cover for 1990 and 2012, derived from CORINE Land Cover(CLC) database, were used to quantify historical forest cover change included in the modelling. To explain the biophysical and anthropogenic effects, this study considered several explanatory factors related to local topography, forest cover pattern, accessibility, urban growth and population density. Using ROC(Receiver Operating Characteristic) and 500 controlling sampling points, the statistical and spatial validations were assessed in order to evaluate the performance of the resulted data. The analysis showed that the area experienced a continuous forest cover change, leading to the loss of over 250,000 ha of forested area during the period 1990–2012. The most significant influence of the explanatory factors of deforestation were noticed in case of distance to forest edge(β=–4.215), forest fragmentation(β=2.231), slope declivity(β=–1.901), elevation(β=1.734) and distance to roads(β=–1.713). The statistical and spatial validation indicates a good accuracy of the model with reasonably AUC(0.736) and Kappa(0.739) values. The model's results suggest an intensification of the deforestation process in the area, designing numerous new clusters with high probability in the Apuseni Mountains, northern and central part of the Eastern Carpathians, western part of the Southern Carpathians and northern part of the Banat Mountains. The study could represent a useful outcome to identify the forests more vulnerable to logging and to adopt appropriate policies and decisions in forest management and conservation. In addition, the resulted probability map could be used in other studies in order to investigate potential environmental implications(e.g. geomorphological hazards or impact on biodiversity and landscape diversity).

Deforestation Trends and Spatial Modelling of its Drivers in the Dry Temperate Forests of Northern Pakistan–A Case Study of Chitral

Deforestation is a major environmental challenge in the mountain areas of Pakistan. The study assessed trends in the forest cover in Chitral tehsil over the last two decades using supervised land cover classification of Landsat TM satellite images from 1992, 2000, and 2009, with a maximum likelihood algorithm. In 2009, the forest cover was 10.3% of the land area of Chitral(60,000 ha). The deforestation rate increased from 0.14% per annum in 1992–2000 to 0.54% per annum in 2000–2009, with 3,759 ha forest lost over the 17 years. The spatial drivers of deforestation were investigated using a cellular automaton modelling technique to project future forest conditions. Accessibility(elevation, slope), population density, distance to settlements, and distance to administrative boundary were strongly associated with neighbourhood deforestation. A model projection showed a further loss of 23% of existing forest in Chitral tehsil by 2030, and degradation of 8%, if deforestation continues at the present rate. Arandu Union Council, with 2212 households, will lose 85% of its forest. Local communities have limited income resources and high poverty and are heavily dependent on non-timber forest products for their livelihoods. Continued deforestation will further worsen their livelihood conditions, thus improved conservation efforts are essential.

Livelihood Economic Activities Causing Deforestation in Northern Ghana: Evidence of Sissala West District

Policymakers and international organizations are making the conscious effort to address climate change through afforestation and sustainable ecosystem management. Economic activities including agriculture, mining, and infra-structure improvement to meet basic human needs continuously degrade the natural and forest resources. The rate of deforestation in Ghana is alarming due to over-reliance on forest resources by forest-dependent communities. Perceived causes of deforestation differ from individuals and groups perspec-tive. This depends on factors including environmental knowledge, education level, market demand and socio-economic activities. Simple random sampling and key informant interview with the aid of semi-structured questionnaire was used to elicit information from the indigenes of Sissala West District to determine their perceptions of causes of deforestation. The study indicated that poverty, high illiteracy, population growth and lack of alternative source of livelihood were the indirect causes which trigger livelihood economic activities such as farming, charcoal burning, wood logging and hunting leading to degradation of the ecosystem. It was also realized that majority of the indigenes are uneducated and this contributes to their unawareness of rate of de-forestation. Recommendations suggested to address challenges were enforce-ment of bye-laws and stringent government environmental policies to deter people from degrading the forest. Education, agroforestry, afforestation, and provision of alternative livelihood were also good interventions suggested.

Land Use Land Cover Change Detection and Deforestation Modeling: In Delomena District of Bale Zone, Ethiopia

Previous studies in Delo-Mena district failed to provide conceptual framework about causes and impacts of deforestation including prediction of spatial location of future deforestation. The study was aimed at investigating spatiotemporal dynamics and prediction of future trends of deforestation in this area. Three periods Landsat images were downloaded and preprocessed using ENVI 4.3. Supervised classification technique was employed for image classification. Land Change Modular used to predict deforestation based on transition between 2000 and 2015 along three driving variables (road distance, settlement and soil). Six land-use land-cover classes were classified for three periods. The result indicated that the forest areas were 91,339, 73,274 and 70,481 hectors in year 2000, 2010 and 2015, respectively. This forest area was reduced by 20% between 2000 and 2010 at annual rate of 2%. Between 2010 and 2015, a forest area was lost by 4% with annual rate of 1%. This deforestation rate was greater than global rates and was lower than rates of south eastern African countries. Farmland expansion was a major cause of deforestation contributed to the annual forest loss by 4.9% and 36% over different periods. In 2030, about 33,243 hectors of a forest area would be expected to disappear that implied emission of about 17 million ton of carbon dioxide. Fuelwoods shortage and loss of biodiversity were perceived as impacts of deforestation. Farm-land and settlement were found increasing at expense of vegetation. Forest plantation, supply of fuel efficient technology and community mobilization were recommended that would be emphasized by the forestry sector based at the district office.

Sensitivity of Amazon Regional Climate to Deforestation

It is known that the Amazon region plays an important role in the global energy, hydrological cycle and carbon balance. This region has been suffering from the course of the past 40 years intense land use and land cover changes. With this in mind, this study has examined possible associations between change in spatial and temporal rainfall variability and land cover change in the Amazon, using the PRECIS regional modelling system. It has been found that the impacts of land cover change by forest removal are more intense in the so-called “Arc of deforestation” over central and southern Amazonia. However, the relative impact of the simulated rainfall changes seems to be more important in the JJA dry season. In addition, the simulations under the deforestation scenarios also show the occurrence of extreme rainfall events as well as more frequent dry periods. Therefore, the results found show to be potentially important in the modulation of regional climate variations which have several environmental and socio-economic impacts.

Deforestation, Agrarian Reform and Oil Development in Ecuador, 1964-1994

Recent biodiversity research in the Western Amazon has emphasized the linkages among road construction, deforestation and loss of indigenous lands. Many observers have concluded that hydrocarbon production inevitably means destruction of forests and expropriation of native territory. Yet evidence from the eastern lowlands of Ecuador (known as the Oriente) shows that oil can be developed without roads or harmful impacts. The Oriente also provides another contrasting case: in areas where no oil was discovered, the government often built roads to support its agricultural colonization efforts. In these areas, a great deal of deforestation and indigenous displacement occurred. Such evidence suggests that a different set of agrarian and environmental policies might permit oil activity without loss of rain forest or indigenous territory.

Deforestation and Habitat Loss: Human Causes, Consequences and Possible Solutions

Deforestation leads to habitat loss while preservation and conservation of the natural forest increase biological diversity.Multiple factors have been reported to be responsible for deforestation and habitat loss,which could either be of human or natural origin.Natural causes of deforestation could be as a result of forest fires,droughts,exotic animals,floods,overpopula­tion of foreign animals and climate change.That notwithstanding,human activities are among the principal causes of global deforestation and habitat loss with agricultural expansion,cattle breeding,timber extraction,mining,oil extraction,dam construction and infrastructure development as some examples of these human influences.This study identifies agricultural ac­tivities and urbanization as the chief causes of human induced deforestation and habitat loss on a large scale.The simple and more practicable approach to curb the already alarming effects of deforestation and habitat loss is through environmental education of everyone still surviving on our planet.Environmental education is the key to reversing continuous and deliberate human actions through the protection of every natural forest and afforesta­tion where necessary.

Exploring perspectives in assessing the quality of governance of the Reducing Emissions from Deforestation and Forest Degradation (REDD+) pilot project in Cambodia: Use of Q Methodology

Public and policy makers alike are concerned about national and global deforestation and forest degradation. These issues pose a significant threat to social, economic and environmental welfare.Attempts to prevent forest loss and increased attention to pilot REDD+ projects in community forestry sites would both deliver rural livelihood benefits and help to reduce adverse climate impacts.However, there has been no significant exploration of the viewpoints of local experts to determine the monitoring and action needed to support communitybased forestry and improve the governance of REDD+pilot projects in Cambodia. Therefore, this study aimed to assess the perceptions of local stakeholders towards the quality of governance of the first community forest REDD+ pilot project in Cambodia,employing Q-methodology. We adapted 11 indicators of the hierarchical framework of assessment of governance quality to design 40 Q-statements related to REDD+ governance or achievements. The 52 P-set ranked these Q-statements with respect to the community-based REDD+ pilot project. Our study revealed that local stakeholders held four distinct, and partially opposite, views, that:(1) the REDD+ project is successful because it is inclusiveness and capable of causing behavioral change;(2) REDD+ pilot projects should be led by government, not external or locally;and needs more resources;(3) the REDD+ pilot project has raised unrealistic expectations, would likely be a source of corruption and will probably not be successful for local people or halting deforestation;and(4) the REDD+ pilot project is inclusive but not very transparent and probably ineffective at protecting forest. Through these four varied perspectives from local people involved in the project,we can see that there remain serious challenges to the future of pilot community forestry REDD+ projects,including the complex interaction between the multinational actors and the local socio-ecological systems.To move forwards, this study suggested Cambodia should make a pro-poor REDD+ program,implementing more community-based REDD+projects which explicitly build the assets and capacity of the poorest households. This study also shows that Q-methodology can highlight the diverse viewpoints of local stakeholders concerning the quality of community forest REDD+ governance, helping policy makers, implementers and local stakeholders to better identify the challenges to be addressed.