Tree Cover Loss Research Articles

Estimation and Study of Forest Loss and Gain Using Spatial Dataset across Districts of Uttarakhand

Aims: To study and estimate the forest cover loss and gain across the 13 districts of Uttarakhand.
 Place and Duration of Study: Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, between September 2021 and December 2021.
 Methodology: We extracted forest cover time-series data from the year 2001 to the year 2020 from Hensen Global Forest Change Dataset. This data was then mapped to the shapefile created in ARC-GIS containing all 13 districts as a Feature Collection, which was then used to individually classify each region and to estimate the size of the loss of tree cover precisely over the district boundary.
 Results: Our study shows forest loss of about (21,05,71,646 square meters) and forest gain of (6,00,79,072 square meters) cumulatively in all the districts of Uttarakhand from the year 2001 to 2020 at a spatial resolution of 30 meters where trees were identified as canopies greater than 5 meters in height.
 Conclusion: Among the districts of Uttarakhand Udham Singh Nagar, Nainital, and Champawat alone contribute to the total tree cover loss area of 15061.7513801 ha. which is about 71.5 % of Uttarakhand’s total tree cover loss. These regions require monitoring and controlling deforestation and more detailed studies like this are required to analyze and prevent the causes of such great-scale deforestation. Analyzing districts apart from those mentioned above, it is observed that the amount of tree cover loss is greater than the reforestation.

Status and Practical Implications of Forest Fire Management in Nepal

Forest fire occurs globally on various scales every year, causing economic, social, ecological, and environmental damage. In a developing country like Nepal, a critical review of policy envisions and its translation concerning the prevailing wildfire scenarios is lacking which is crucial for sustainable forest fire management. We examine the existing disaster management policies relevant to forest fire, and analyse forest fire incidences and their impact on forest cover loss and eCO2 (equivalent carbon dioxide) emissions using the data from Global Forest Watch (GFW) between 2001 to 2021. We also assessed public finance scenarios for forest fire management in Nepal and correlated and compared these data with each other. Our results find that the ‘Forest Fire Management Strategy 2010’ is the only comprehensive policy document that guides forest fire management in Nepal. Despite having low political and financial support (dedicated forest fire management budget is <0.5 per cent out of all forestry sector), awareness raising programme such as celebration of forest fire management week, broadcasting awareness raising messages and information, use of forest firefighting tools and equipements are some of the ground level interventions to prevent and control forest fire. GFW data shows that 29443 visual infrared imaging radiometer suite (VIIRS) fire alerts record (available only for 2012 to 2021), burns 207956.5 hectares (ha) area, 3.28 ha of forest cover loss, and 1132 Mg eCO2 emissions every year on average. These figures are 0.07 per cent, 0.05 per cent, and 0.0176 per cent compared to total forest cover loss, total emission (eCO2) from the forest, and proportion of tree cover loss to burnt area, respectively. Results entail that the existing forest fire management policy requires a revisit considering the changed national and international context, forest fire should be considered as a high priority by all sectors and actors because of its widespread socio-economic, ecological, and environmental impacts. Ignorance of forest fire management could severely hinder the target for national and international commitments including performance-based carbon trading and maintaining forest cover. The findings would provide insights for policy decisions to manage forest fires sustainably.

TOWARDS A TREE COVER CHANGE EARLY WARNING SYSTEM BASED ON SENTINEL-1 DATA AND A NEURAL NETWORK ARCHITECTURE

Abstract. This study aimed at exploring the potential of neural networks composed of convolutional and Long Short-Term Memory (LSTM) layers to handle dense Sentinel-1 data time series to develop a tree cover loss Early Warning System (EWS). The study area was in the Madre de Dios region in Peru that hosts a humid tropical forest. The second objective of this study was to investigate the potential of large free open-source datasets such as those from the GLAD and Geobosques alerts to calibrate and validate the models. The study demonstrated the capacity of the tested NN models to improve the detection of tree cover loss compared to a classical random forest algorithm thanks to their capacity to handle explicitly both spatial and temporal data. The accuracies of the best model compare reasonably well with those from similar studies. However, the observed overestimation of the Cover-loss class in the output map can be mainly linked to the quality of the alert datasets used as input data. Avenues to overcome the identified limits of this preliminary study are presented. This work provides a solid knowledge basis on the potential of a NN-based EWS and opens potential avenues for further improvements.

Coupled forest zoning and agricultural intervention yields conflicting outcomes for tropical forest conservation in the Democratic Republic of the Congo (DRC)

Agricultural intensification and forest conservation are often seen as incompatible. Agricultural interventions can help boost food security for poor rural communities but in certain cases can exacerbate deforestation, known as the rebound effect. We tested whether coupling agricultural interventions with participatory forest zoning could improve food security and promote forest conservation in the Democratic Republic of the Congo. Simple agricultural interventions led to a >60% increase in cassava yields and a spill-over effect of improved cassava variety uptake in non-intervention zones. Household surveys conducted at the end of the 8 year project implementation period revealed that households that received agricultural interventions had more favorable attitudes toward forest zoning and conservation. The surveys also showed that farmers in the intervention domain practiced less land-intensive field and fallow management strategies compared to those practiced in the non-intervention domain. However, an 18 year time series analysis of Landsat satellite data revealed that agricultural expansion persisted in areas both with and without intervention assistance, and there is risk of a rebound effect. Approximately 70% of the tree cover loss that occurred outside of the agricultural areas was located within a 3 km buffer zone surrounding the outermost edges of the agricultural areas, which suggested that the majority of tree cover loss was caused by agricultural expansion. Within that 3 km buffer, average annual tree cover loss during the post-intervention period was higher in the intervention domain compared to the non-intervention domain (0.17% yr−1 compared to 0.11% yr−1 respectively, p < 0.001), suggesting risk of a rebound effect. The disconnection between household perceptions of zoning adherence and actual behavior indicates the importance of strengthening governance structures for community-based monitoring and enforcement.

Half-Century of Forest Change in a Neotropical Peri-Urban Landscape: Drivers and Trends

Neotropical forested landscapes have become agricultural areas and human settlements, causing forest fragmentation, land degradation, and habitat loss. Nonetheless, complex tree cover loss and recovery processes may occur even while urban areas expand. Biophysical, social, political, and economic drivers influence forest loss or recovery over time. This study analyzes land-use change dynamics in urban and peri-urban landscapes in the western sector of Xalapa City between 1966–2018 and identifies the primary drivers that have played a significant role in deforestation and forest recovery processes. The main finding denotes the city’s expansion between 1966 and 2018, initially covering 8% of the study area and increasing to 27%. However, between 1966 and 2018, 15% of forest cover was lost in net terms, a finding ascribed to forest recovery in some abandoned areas. Social and biophysical variables significantly influenced deforestation and forest recovery trends, and few variables were singular to one process. The deceleration of forest loss and accomplishing tree cover recovery are possible in some urban settings. In this context, green urban and peri-urban landscapes become strategic to achieve more sustainable cities. Among other benefits, green areas provide landscape connectivity, temperature regulation, air quality improvement, noise dampening, and recreational areas.

Predicting wasteful spending in tree planting programs in Indian Himalaya

Tree planting is widely promoted as a cost-effective natural climate solution, yet there are few evaluations of the implementation of tree planting. Our analysis of a unique dataset on tree planting in the Indian Himalayan state of Himachal Pradesh shows that over half of the state’s budget for tree planting is wasted on plantations that are unlikely to survive and/or are poorly designed to achieve the state’s goal of increasing forest cover. Himachal Pradesh (and India more generally) has been identified as a high potential area for natural climate solutions due to high government capacity, adequate funding, and government agencies with extensive planting experience. We combine data on the location and financial outlay for plantations, which allow us to analyze the relationship between plantations and social and biophysical conditions, with a machine learning model, trained on past land cover change, which predicts the likelihood of future tree cover loss in plantation areas. Our finding that even in this high potential area tree planting programs involve considerable wasted expenditure on ineffective plantations raises questions about optimistic assessments of the potential for tree planting to serve as a cost-effective natural climate solution. We suggest deemphasizing the target-based approaches that dominate present policy-making and high-profile scientific publications, which we argue are the cause of wasted expenditures in Himachal Pradesh. Instead policy-makers and scientists interested in natural climate solutions should focus on developing solutions that respond to local biophysical, social, and economic realities, and are implemented through transparent procedures that increase accountability to and reinforce the rights of forest dependent people.

A Continental Assessment of the Drivers of Tropical Deforestation With a Focus on Protected Areas

Deforestation contributes to global greenhouse gas emissions and must be reduced if the 1.5°C limit to global warming is to be realized. Protected areas represent one intervention for decreasing forest loss and aiding conservation efforts, yet there is intense human pressure on at least one-third of protected areas globally. There have been numerous studies addressing the extent and identifying drivers of deforestation at the local, regional, and global level. Yet few have focused on drivers of deforestation in protected areas in high thematic detail. Here we use a new crowdsourced data set on drivers of tropical forest loss for the period 2008–2019, which has been collected using the Geo-Wiki crowdsourcing application for visual interpretation of very high-resolution imagery by volunteers. Extending on the published data on tree cover and forest loss from the Global Forest Change initiative, we investigate the dominant drivers of deforestation in tropical protected areas situated within 30° north and south of the equator. We find the deforestation rate in protected areas to be lower than the continental average for the Latin Americas (3.4% in protected areas compared to 5.4%) and Africa (3.3% compared to 3.9%), but it exceeds that of unprotected land in Asia (8.5% compared to 8.1%). Consistent with findings from foregoing studies, we also find that pastures and other subsistence agriculture are the dominant deforestation driver in the Latin Americas, while forest management, oil palm, shifting cultivation and other subsistence agriculture dominate in Asia, and shifting cultivation and other subsistence agriculture is the main driver in Africa. However, we find contrasting results in relation to the degree of protection, which indicate that the rate of deforestation in Latin America and Africa in strictly protected areas might even exceed that of areas with no strict protection. This crucial finding highlights the need for further studies based on a bottom up crowdsourced, data collection approach, to investigate drivers of deforestation both inside and outside protected areas.

Relating Country-Level Governance and Tree Cover Loss in Sub-Saharan African Protected Areas: Identifying Knowledge Gaps and a More Nuanced Perspective

‘Good governance’ is highlighted by many as being essential for improving protected area (PA) management and conservation outcomes, with a growing body of evidence based on site-level governance data. Yet how exactly governance at other levels supports or hinders successful PA implementation, and how this should be considered in conservation planning and practice, remains insufficiently understood. We conducted an exploratory analysis of the relationship between the quality of country-level governance and trends in tree cover loss within sub-Saharan African PAs. For the period 2008–2017, we correlated annual governance scores from the Ibrahim Index of African Governance (IIAG) with the annual rate of tree cover loss in the total terrestrial area of PAs in 33 forested sub-Saharan African countries. Overall governance was not correlated with tree cover loss in a simple model, but there was evidence that overall governance was positively correlated with tree cover loss in PAs when the interaction with environmental governance was included. The interaction indicated that the rate of tree cover loss decreased for a given level of overall governance as environmental governance increased. Human development was negatively correlated with forest loss. Thus, the relationship between country-level ‘good governance’ and conservation success is more complex than a direct and positive cause and effect. Yet, uncertainty remains about the many possible and likely confounding pathways: whilst the quality of overall governance may be mirrored at the site-level, it may also contribute to increased anthropogenic pressures on natural resources. Through this research we found significant limitations in data quality and availability both to evaluate the effectiveness of protection beyond tree cover, as well as less conventional governance aspects, such as environmental policy and regulation or site-level governance. With an expected increase in area-based protection and conservation financing in the coming decades, such data will be vital to monitor the effectiveness of our efforts and ensure financial accountability.

Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series

Sample-based estimates augmented by complete coverage land-cover maps were used to estimate area and describe patterns of annual land-cover change across the conterminous United States (CONUS) between 1985 and 2016. Most of the CONUS land cover remained stable in terms of net class change over this time, but a substantial gross change dynamic was captured by the annual and cumulative time intervals. The dominant types of changes can be grouped into natural resource cycles, increases in urbanization, and surface-water dynamics. The annual estimates over the 30-year time series showed a reduction in the rate of urban expansion after 2006, new growth in cropland after 2007, but a net overall decline in cropland since 1985, and two eras of net tree cover loss, the first one early in the time series and the second starting in 2012. Our study provides a holistic assessment of the CONUS land-cover conversion (class) change and can serve as a new benchmark for future research.

Characterization of the hydro-geological regime of fractured aquifers in Benin (West-Africa) using multi-satellites and models

Study regionFractured aquifers in Benin have emerged in the past decades as a critical resource because of the increasing domestic water needs, agriculture, and livestock breeding. Hence this study was undertaken in the poorly gauged and complex basement aquifers beneath the 9th latitude. Study focusTo aid water resources management and sustainability, this study combined satellite remote sensing products with outputs from hydrological models and in situ measurement to assess the spatial and temporal patterns of water storage changes, including groundwater. The fractured aquifers’ hydrogeological regime is further analysed through monitoring wells’ series interpretation. New hydrological insights for the regionResults show considerable inter-annual variations in Terrestrial Water Storage (TWS) during the study period (2003–2019). Two uptrend intervals characterized by wet hydrological seasons from 2006 to 2013 and 2016–2019 with respectively, Sen’s slope values of 1.16 mm/yr and 4.47 mm/yr were observed. However, two downtrend intervals represented by dry hydrological seasons with Sen’s slopes of − 1.01 mm/yr (2003–2006) and − 1.19 mm/yr (2013–2016) were also observed. The inter-annual seasonality in land water storage components showed that unlike the 4 climatic seasons, the hydrogeological regime is affected by 3 seasons each year. The first dry season takes place from January to April-May (−29.1 ± 17.7 mm/yr) followed by the wet season (April-May to October-November: 41.6 ± 26.4 mm/yr) and the last dry period, which is stronger (November to December: −53.7 ± 31.6 mm/yr). Soil moisture (SM) and canopy water content (CW) declined during the 2008–2016 period, coinciding with decline in Tree cover areas, which dropped by 25.5% (3086.7 sqkm). Further from 2007 to 2014, the four monitoring wells have seen the groundwater level increased by, 1.44 m/yr, 2.0 m/yr, 3.2 m/yr, and 0.56 m/yr for the Affon, Zou, Okpara and Couffo sub-basins, respectively. The retrieved TWS and Water ‐ Global Assessment and Prognosis groundwater storage (WaterGap-GWS) sub-domains based on statistical decomposition was used to identify hidden patterns to improve knowledge on the climatic and hydrological conditions, which affected land water storage. Moreover, TWS, GWS and SM lost water 51%, 57% and 47% of the time, respectively, during the period and the storage potential is lower for the aquifers compared to the unsaturated zone. Precipitation is recognized as a primary driver of GWS (r = 0.69; α = 0.05) in the region and a change in GWS is more likely to drive the CW and affect the vegetation greenness. Moreover, the anthropogenic pressure exacerbates Tree cover loss. Additionally, the Extra Tree regressor performs best in the groundwater storage change ∆GWS prediction with a strong and positive Pearson Correlation Coefficient of 0.92. The basement aquifers assessment using the aforementioned approach has potential to support large-scale monitoring efforts for more reliable water resources management in the region.

Sustainable Urban Forest Conservation: Assessing Public Attitudes towards Urban Forests in Nairobi City

Nairobi city’s rapid development has caused urban tree cover loss despite evidence of demand, and values attached to these forests by the residents. This paper investigated these values through an analysis of the residents’ attitudes towards the urban forests. Data on urban forest characteristics, composition, problems, causes, and proposed solutions were collected through open ended questions and attitudinal values using a 7-point Likert psychometric scale questionnaire with 40 attitude statements. The findings on urban forest character, problems, causes, and solutions were ranked in order of popularity while attitudes were subjected to a Relative Importance Index (RII) analysis which ranked them in order of importance. The factor “Trees make the city beautiful” ranked as the most important variable (RII = 0.9457), followed by “Urban forests protect the city against climate change effects” (RII = 0.9228). The variable “Forests in the city should be cleared to provide more land for housing” factor was ranked as the lowest (RII = 0.2069). The study recommends that Nairobi’s urban forest conservation strategies recognize and prioritize resident’s values through participatory conservation strategies. In addition, adoption of the identified proposals, improvements and suggestions in the order tabulated in this paper will promote forest conservation.

The Environmental Kuznets Curve for Deforestation in Indonesia

This study provides empirical findings on the relationship between deforestation and income in 32 provinces in Indonesia. To enrich the discussion on deforestation, this study investigates the impact of the factors of population, roundwood production, land area, and main crop production on deforestation. The selected main crops in Indonesia are oil palm, coffee, coconut, rubber, and cacao. The results confirm the existence of the EKC relationship between deforestation and income in Indonesia. The study also finds that oil palm production positively affects tree cover loss, but the production of natural rubber has the opposite impact on deforestation.

Clarifying the Smokescreen of Russian Protected Areas

Although in strictly protected areas no forest management and logging activities should be evident, a preliminary study detected that, even in the 200 areas with the highest protection of Russia, more than 2 Mha of trees have been lost between 2001 and 2018. Nonetheless, a relevant percentage of the actual drivers of tree loss in Russian strictly protected areas was surrounded by uncertainties due to several factors. Here, in an attempt to “clarify the smokescreen of Russian protected areas”, by validating previous remotely sensed data with new high-resolution satellite imagery and aerial images of land-use change, we shed more light on what has happened during the last 20 years. We used the same layer of tree loss from 2001 to 2020 but, instead of intersecting it with the MODIS data that could have been a source of underestimation of burned surfaces, we overlapped it to the layer of tree cover loss by dominant driver. We analysed the main drivers of tree loss in almost 200 strictly protected areas of Russia. We found that although fire is responsible for 75% of the loss in all strictly protected areas, forestry activities still account for 16%, and 9% is due to undefined causes. Therefore, uncontrolled wildfires (including those started before or after logging) and forestry activities are the main causes of 91% of the total tree loss. The combination of wildfires (often started intentionally) and forestry activities (illegally or barely legally put in place) caused a loss of an astonishing 3 million hectares. The fact that ≈10% of Russian tree cover was lost in two decades since 2001 only in strictly protected areas requires high attention by policymakers and important conservation actions to avoid losing other fundamental habitats and species during the next years when climate change and population growth can represent an additional trigger of an already dramatic situation. We call for an urgent response by national and local authorities that should start actively fighting wildfires, arsonists, and loggers even in inhabited remote areas and particularly in those included in strictly protected areas.

Evaluating Recent and Future Climatic Suitability for the Cultivation of Norway Spruce in the Czech Republic in Comparison with Observed Tree Cover Loss between 2001 and 2020

The high portion of secondary Norway spruce in Central European forests constitutes a major problem because a significant part of these forests is moving further away from their original bioclimatic envelope. The precise evaluation and prediction of climatic suitability are needed for the implementation of forest adaptation strategies. We evaluated climatic suitability for the cultivation of Norway spruce in the Czech Republic forests, making use of the Random Forest combined learning statistical method. The evaluation presented was based on a comparison with the climatic normal period 1961–1990; change analysis was carried out for the period 1991–2014 and projected for 2021–2040 and 2041–2060. We found that suitable conditions for Norway spruce will remain only in 11.3% by area of Czech forests in the period 2041–2060 vs. 46.0% in the period 1961–1990. We also compared tree cover loss data (using Global Forest Watch) from 2001 to 2020 with statistics on salvage logging. In the period, the cover loss affected 19.5% of the area with more than 30% Norway spruce. The relationships between relative tree cover loss and the percentage of salvage logging caused by insects were conclusive and statistically significant.

Agriculture is the primary driver of tree cover loss across the Forestière region of the Republic of Guinea, Africa

Biodiversity hotspots are conservation priority areas that feature exceptionally high levels of species endemism and high levels of habitat loss. The Guinean Forests of West Africa hotspot, home to a quarter of all the mammal species of Africa, has experienced high levels of forest loss within its protected areas. Here, we analyzed tree cover loss and its proximate drivers within Guinée Forestière, a high biodiversity region within the Guinean Forests of West Africa hotspot, both inside and outside protected areas. Using Landsat analysis ready data and a regionally calibrated, annual forest change detection model, we mapped tree cover loss occurring across this region from 2000 to 2018. We quantified the area of tree cover loss and identified proximate drivers using a statistical sample of reference data. The total tree cover loss in Guinée Forestière between years 2000 and 2018 was 10,907 km2 (SE 889 km2), which consists of approximately 25% of the region’s total land area. Of this total loss, 364 km2 (SE 91 km2) occurred within protected areas of high biodiversity value. Tree cover loss was not consistent across high biodiversity areas and did not appear to be related to protected area classification. Smallholder agriculture (subsistence and cash crop farming) was the primary driver of tree cover loss across Guinée Forestière. This research provides multitemporal spatial data on tree cover dynamics that is required for effective implementation of sustainable management and biodiversity conservation strategies within the broader socioecological landscape of Guinée Forestière. We also highlight important limitations to consider and address when using remote sensing to automate change detection across landscapes.

Assessing mangrove deforestation using pixel-based image: a machine learning approach

Mangrove is one of the most productive global forest ecosystems and unique in linking terrestrial and marine environment. This study aims to clarify and understand artificial intelligence (AI) adoption in remote sensing mangrove forests. The performance of machine learning algorithms such as random forest (RF), support vector machine (SVM), decision tree (DT), and object-based nearest neighbors (NN) algorithms were used in this study to automatically classify mangrove forests using orthophotography and applying an object-based approach to examine three features (tree cover loss, above-ground carbon dioxide (CO2) emissions, and above-ground biomass loss). SVM with a radial basis function was used to classify the remainder of the images, resulting in an overall accuracy of 96.83%. Precision and recall reached 93.33 and 96%, respectively. RF performed better than other algorithms where there is no orthophotography.

Northernmost European spruce bark beetle Ips typographus outbreak: Modelling tree mortality using remote sensing and climate data

Acute or chronic drought stress caused by climate change can contribute to the weakening of forest ecosystems and lead to extensive bark beetle infestations. Siberian spruce (Picea obovata Ledeb.) forests of the Dvinsko-Pinegskiy, a natural reserve in the Arkhangelsk region, Russia, have been subject to unprecedented tree cover loss caused by the Eurasian spruce bark beetle (Ips typographus L.) in the last two decades. This is the first recorded case of such an extensive outbreak of Ips typographus occurring at higher latitudes. We used remote sensing and climate data to model and compute annual tree-loss change due to natural factors, with a focus on bark beetle outbreaks, over a 14-year period (2001–2014). Usinglinear regression models, we found a combination of average annual temperature and precipitation, temperature and precipitation in June, to be the most important drivers of annual tree-loss.

The impact of tree loss on carbon management in West Africa

This study quantifies the amount of carbon stored and sequestered by vegetation in west Africa, carbon loss due to tree cover loss, and the potential natural sequestration relative to projected carbon emissions in 2030. GIS analysis of published data on vegetation biomass, tree cover, sequestration by vegetation and soil carbon indicate that vegetation and soil held 38,855 Mt of carbon in 2010, most of which was in above and below ground vegetation. The loss of 58,353 km2 (9%) of tree cover between 2010 and 2018 resulted in the loss of 672 Mt of 14,923 Mt carbon in vegetation. Key Biodiversity Areas, (sites of conservation importance), covered 7.4% of land but in 2010 contained 16% of carbon stored in vegetation. Trees sequestered between 23.6 and 53.6 Mt of carbon in 2018 (17% of which was in Key Biodiversity Areas). Restoration of the tree cover lost in west Africa between 2010 and 2018 could sequester an additional 27.5 Mt of carbon per annum during the first 30 years of growth. Our estimates indicate a combination of conservation and restoration of tree cover could sequester the equivalent of c.30% of projected 2030 regional emissions, contributing significantly towards mitigating climate change.

Assessing Drivers of Forest Conservation in Simancuang Village Forest, West Sumatra

This study empirically assessed Social Forestry program implementation in Simancuang Village Forest or locally known as Hutan Nagari (HN) Simancuang in West Sumatra, Indonesia. We performed two analyses using primary and secondary data, namely propensity score matching to estimate the effects of the enactment of HN Simancuang in 2012 on forest cover loss and ordinal logistic regression (OLR) to predict the determinants of conservation awareness. The results of the forest cover analysis showed that forest cover loss in HN Simancuang between 2012 and 2019 was 0.038 percentage point lower than the adjacent protection forest. The relatively small impact was meaningful because although HN Simancuang is located much closer to settlements which increases the pressure on the forest, it could still maintain lower tree cover losses than the adjacent protection forest. This result indicated a certain degree of conservation awareness among HN Simancuang members, which prompted us to conduct a survey to 111 individuals from different households. To do this, we used the Ecosystem Services framework to conceptualise conservation awareness in HN Simancuang. Our OLR results showed that regulating and provisioning services of forests are the strong determinants of conservation awareness among the individuals in our sample. Our study indicates the need to implement social forestry program monitoring and evaluation, improve access to facilitation, and enhance agroforestry practice as the means to increase conservation awareness among forest-dwelling communities.

Tree Cover Loss in the Mediterranean Region—An Increasingly Serious Environmental Issue

The Mediterranean Region currently faces major environmental issues that require constant analysis and monitoring. This study presents a thorough approach based on the application of Landsat imagery from Global Forest Change during 2001–2019. Spatial distribution mapping was one of the objectives of the study. We approached the analysis of tree cover loss areas by analyzing the cumulative tree cover loss and Tree Cover Loss Rate. This indicator offers information about the trend of tree cover loss in each Mediterranean country. A total of 581 Mha of deforested area was mapped during the analyzed period. Analysis was further supplemented by some statistical operations (distributions shown via histograms, validation via Shapiro–Wilk normality test, and testing via one-sample t-test). Agricultural expansion, intense forest fires, illegal logging, overgrazing (especially in the northern part of Africa), and extensive livestock farming have influenced the Mediterranean forest ecosystem’s stability. The continuation of these activities could cause extreme climatic events, severe degradation, and desertification.