Deforestation and Forest Degradation as an Environmental Behavior: Unpacking Realities Shaping Community Actions

Sustainable Development versus Extractivist Deforestation in Tropical, Subtropical, and Boreal Forest Ecosystems: Repercussions and Controversies about the Mother Tree and the Mycorrhizal Network Hypothesis

This research reviews the phenomenon of extractive deforestation as a possible trigger for cascade reactions that could affect part of the forest ecosystem and its biodiversity (surface, aerial, and underground) in tropical, subtropical, and boreal forests. The controversy and disparities in criteria generated in the international scientific community around the hypothesis of a possible link between "mother trees" and mycorrhizal networks in coopetition for nutrients, nitrogen, and carbon are analyzed. The objective is to promote awareness to generate more scientific knowledge about the eventual impacts of forest extraction. Public policies are emphasized as crucial mediators for balanced sustainable development. Currently, the effects of extractive deforestation on forest ecosystems are poorly understood, which requires caution and forest protection. Continued research to increase our knowledge in molecular biology is advocated to understand the adaptation of biological organisms to the new conditions of the ecosystem both in the face of extractive deforestation and reforestation. The environmental impacts of extractive deforestation, such as the loss of biodiversity, soil degradation, altered water cycles, and the contribution of climate change, remain largely unknown. Long-term and high-quality research is essential to ensure forest sustainability and the preservation of biodiversity for future generations.

Land Use Land/Cover Change Reduces Woody Plant Diversity and Carbon Stocks in a Lowland Coastal Forest Ecosystem, Tanzania

The East-African lowland coastal forest (LCF) is one of Africa’s centres of species endemism, representing an important biodiversity hotspot. However, deforestation and forest degradation due to the high demand for fuelwood has reduced forest cover and diversity, with unknown consequences for associated terrestrial carbon stocks in this LCF system. Our study assessed spatio-temporal land use and land cover changes (LULC) in 1998, 2008, 2018 in the LCF ecosystem, Tanzania. In addition, we conducted a forest inventory survey and calculated associated carbon storage for this LCF ecosystem. Using methods of land use change evaluation plug-in in QGIS based on historical land use data, we modelled carbon stock trends post-2018 in associated LULC for the future 30 years. We found that agriculture and grassland combined increased substantially by 21.5% between the year 1998 and 2018 while forest cover declined by 29%. Furthermore, forest above-ground live biomass carbon (AGC) was 2.4 times higher in forest than in the bushland, 5.8 times in the agriculture with scattered settlement and 14.8 times higher than in the grassland. The estimated average soil organic carbon (SOC) was 76.03 ± 6.26 t/ha across the entire study area. Our study helps to identify land use impacts on ecosystem services, supporting decision-makers in future land-use planning.

Land use and land cover dynamics and traditional agroforestry practices in Wonchi District, Ethiopia

BACKGROUND

Investigating the land use and land cover (LULC) dynamics and the status of traditional agroforestry practices provide important data for policymakers. The main objective of this study was to assess the LULC dynamics and traditional agroforestry practices among smallholder farmers across the two agro-ecological zones in Wonchi District of Ethiopia.

METHODS

Landsat images were acquired from Earth Explorer, and changes in LULC were quantified with three Landsat sensors in the three time-series (1985, 2001, and 2019). Supervised classification with maximum likelihood technique was employed using ERDAS Imagine and ArcGIS. A ground survey was conducted with 100 key informants who were selected from 10 sites using a purposive sampling method. The collected data were subjected to direct matrix ranking, use-value analysis of most important multipurpose plant species, and semi-structured interviews were conducted for qualitative analysis.

RESULTS

In total, 103 agroforestry plant species belonging to 44 families were identified in Wonchi District, of which 74 were indigenous including seven endemic and 29 exotic species. The highest species (13) were recorded in the Fabaceae family. About 61% of species were reported in the midland agro-ecological zone. A mixed farming system was the most frequently (56%) reported source of income. The results of LULC changes from 1985 to 2019 showed that the agroforestry cover increased from 31.1% to 34.9% and settlement including road construction increased from 12.5% to 31.6% of the total area with an annual rate change of 0.3% and 2.7%, respectively. These changes corresponded with a decreasing trend of the forest, cropland, water body, and shrub at a rate of 4.7%, 1.3%, 0.8%, and 0.5%, respectively. The LULC changes were more pronounced in the highlands than in the midlands of Wonchi District. Expansion of settlement and tenure policy change are the main drivers for these changes in the area. The authors recommended that protecting and planting indigenous and multipurpose plant species is essential as restoration techniques for all degraded land-use types. Therefore, strengthening agroforestry practices and land-use planning is urgently needed for achieving multiple goals.

A Bibliometric and Visual Analysis of Environmental Behavior Research

Environmental behavior has become one of the most important research areas in the field of sustainable development in recent years. Based on 818 papers on environmental behavior in the Web of Science database from 2002 to 2020, this paper uses CiteSpace software to analyze the trends in publication, subject categories, influential authors and journals, countries, and institutional collaborations. The results show that environmental behavior research has steadily increased over the past 19 years and has gradually achieved diversity and intersection in research subjects. The research on environmental behavior is mainly distributed in the United States, China, and European countries, with the United States being the largest contributor in the field and at the center of the institutional collaboration network. The present research hotspots are as follows: the concept of environmental behavior, factors affecting environmental behavior, the dimension division of environmental behavior, and the construction of a sustainable environmental behavior model. The sustainable development, predictive environmental behavior indicators, factors that affect environmental behavior, and the construction of theoretical models of environmental behavior will become future research trend.

Towards a green economic policy framework in China: role of green investment in fostering clean energy consumption and environmental sustainability

Recently, China has relished rapid green investment, and its influence on clean energy consumption and environment is substantial. Therefore, this study scrutinizes the effects of green investment on clean energy consumption and CO2 emissions in China by using autoregressive distributed lag model (ARDL) approach over time from 1998 to 2019. The results show that green investment tends to have a positive effect on clean energy consumption in China in the long run. The outcomes of study also show that green investment also tends to have a negative effect on CO2 emissions in China, but it has a small effect on carbon emissions in magnitude in the long run. Importantly, possible channels revealed green investment encouraging consumers and producers to consume clean energy, thereby positively affecting the environmental quality in China. Other control variables' findings show that environmental tax and financial development have increased the environmental quality by decreasing the CO2 emissions. Based on the findings, it recommends that green investment is considered necessary for encouraging clean energy consumption to reduce carbon emissions in high pollutant economies.

Multi-layer perceptron-Markov chain-based artificial neural network for modelling future land-specific carbon emission pattern and its influences on surface temperature

Reliable and accurate environmental state prediction can help in long-term sustainable planning and management. Enormous land-use/ land-cover (LULC) transformation has been increasing the carbon emissions (CEs) and land surface temperature (LST) around the world. The study aimed to (i) examine the influences of land specific CEs on LST dynamics and (ii) simulate future potential LULC, CEs and LST pattern of Khulna City Corporation. Landsat satellite images of the year 2000, 2010 and 2020 were used to derive LULC, LST and CEs pattern and change. The correlation between land-use indices (NDBI, NDVI, NDWI) and LST was examined to explore the impacts of LULC change on LST. Unplanned urbanization has increased 11.79 Km2(26.10%) buildup areas and 25,268 tons of CEs during 2000–2020. The calculated R2 value indicates the strong positive correlation between CEs and LST. To simulate the future LULC, CEs and LST pattern for the year 2030 and 2040, multi-layer perceptron-Markov chain (MLP-MC)-based artificial neural network model was utilized with the accuracy rate of 94.12%, 99% and 98.48% for LULC, LST and CEs model, respectively. The simulation shows that by 2040, buildup area will increase to 87.33%, net CEs will increase by 19.82 × 104tons, and carbon absorptions will decrease by 23. 55 × 104tons and 69.54% of the total study area's LST will be above 390C. Such predictions signify the necessity of implementing a sustainable urban development plan immediately for the sustainable, habitable and sound urban environment.

Incentives for landscape restoration: Lessons from Shinyanga, Tanzania

Owing to high rates of land and forest degradation, there is consensus that forest landscape restoration is a global priority with the Bonn Challenge and the New York Declaration on Forests committing to restore about 350 Million hectares by 2030, globally. However, there is a need for incentives that motivate these restoration efforts and disincentives aimed at restricting activities that result in further land degradation. We provide insights and understanding of the incentives and disincentives measures applied within the forest restoration systems through a case study in the Shinyanga region of Tanzania. Incentives that have promoted forest landscape restoration in Shinyanga include; conservation benefits, education and information, Reducing Emissions from Deforestation and forest Degradation (REDD+), well-defined property rights & increasing land prices and awards while disincentives include; penalties, quotas and permits. Intrinsic incentives that are derived from self-desire within an individual such as conservation benefits and education & information were more preferred within Shinyanga region compared to extrinsic incentives which relied more on external factors such as REDD+ and awards. Nonetheless, a combination of both incentives and disincentives has led to the success of restoration in Shinyanga; positive incentives worked better for privately owned lands while regulatory disincentives worked better for communally owned restoration lands. High levels of social equity and trust have enabled the functioning of these incentives while a robust governance structure at the local level has been instrumental in enforcing the disincentives. There is need for government and all stakeholders to maintain and enhance the gains from restoration, especially empowering communities further, for these incentives to work.

Predicting Behavioral Intention of Rural Inhabitants toward Economic Incentive for Deforestation in Gilgit-Baltistan, Pakistan

The conservation of forest in the northern areas of Pakistan is the major priority of the national environmental policy to fight against global warming. Despite the policy for the protection of forest, rural residents’ behavior toward economic incentives for deforestation may undermine their conservation goals. Therefore, the purpose of this study was to understand the factors that affect the illegal behaviors related to deforestation in the northern areas of Pakistan. The present study applied the socio-psychological theory of planned behavior to predict the behavioral intention of rural residents toward economic incentives for deforestation. Correlations were explored between background factors toward motivations for deforestation based on positive and negative views through open-ended questions. Attitude and descriptive norm were found good predictors to perceive the behaviors. The findings of the study suggest that rural communities’ support for compliance with policies is vital for the long-term efficacy and protection of the forest in the region. Further, change in the behaviors of inhabitants toward the ecosystem through training can be improved to manage the forest.

How China is fostering sustainable growth: the interplay of green investment and production-based emission

To mitigate environmental problems and to achieve sustainability, China is striving to transition to low-carbon urban economies. Among several significant steps, the country has made remarkable success in controlling the emissions from transportation, buildings, and energy by shutting down or relocating several polluting industries. This study contributes to the issue of sustainable growth debate using time series data from China for the period 1998-2017 and empirically examines the effects of green investment and renewable energy consumption on production-based carbon emissions for China. The strength of this study is that it tested some new variables such as production-based carbon emissions and green investment. Using autoregressive distributed lag model (ARDL) cointegration technique, we found that production-based emission and its determinants move together in the long run. The study found that green investment and renewable energy consumption are both helpful in controlling production-based carbon emissions, while trade openness increases production-based carbon emissions. Hence, green investment and renewable energy consumption contribute to the achievement of sustainable growth. Moreover, based on a robustness check, human capital, financial development, and environment-specific technological innovation are found to be helpful in curbing production-based carbon emissions. Our study recommends financial technology (fin-tech), green investment, and public-private partnership investment in renewable energy to mitigate the effect of production-based carbon emissions.

Direct measurement forest carbon protocol: a commercial system-of-systems to incentivize forest restoration and management

Forest carbon sequestration offsets are methodologically uncertain, comprise a minor component of carbon markets and do not effectively slow deforestation. The objective of this study is to describe a commercial scale in situ measurement approach for determination of net forest carbon sequestration projects, the Direct Measurement Forest Carbon Protocol™, to address forest carbon market uncertainties. In contrast to protocols that rely on limited forest mensuration, growth simulation and exclusion of CO₂ data, the Direct Measurement Forest Carbon Protocol™ is based on standardized methods for direct determination of net ecosystem exchange (NEE) of CO₂ employing eddy covariance, a meteorological approach integrating forest carbon fluxes. NEE is used here as the basis for quantifying the first of its kind carbon financial products. The DMFCP differentiates physical, project and financial carbon within a System-of-Systems™ (SoS) network architecture. SoS sensor nodes, the Global Monitoring Platform™ (GMP), housing analyzers for CO₂ isotopologues (e.g., ¹²CO_2, ¹³CO₂, ¹⁴CO₂) and greenhouse gases are deployed across the project landscape. The SoS standardizes and automates GMP measurement, uncertainty and reporting functions creating diverse forest carbon portfolios while reducing cost and investment risk in alignment with modern portfolio theory. To illustrate SoS field deployment and operation, published annual NEE data for a tropical (Ankasa Park, Ghana, Africa) and a deciduous forest (Harvard Forest, Petersham, MA, USA) are used to forecast carbon revenue. Carbon pricing scenarios are combined with historical in situ NEE annual time-series to extrapolate pre-tax revenue for each project applied to 100,000 acres (40,469 hectares) of surrounding land. Based on carbon pricing of $5 to $36 per ton CO₂ equivalent (tCO₂eq) and observed NEE sequestration rates of 0.48 to 15.60 tCO₂eq acre^-1 yr^-1, pre-tax cash flows ranging from $230,000 to $16,380,000 across project time-series are calculated, up to 5×  revenue for contemporary voluntary offsets, demonstrating new economic incentives to reverse deforestation. The SoS concept of operation and architecture, with engineering development, can be extended to diverse gas species across terrestrial, aquatic and oceanic ecosystems, harmonizing voluntary and compliance market products worldwide to assist in the management of global warming. The Direct Measurement Forest Carbon Protocol reduces risk of invalidation intrinsic to estimation-based protocols such as the Climate Action Reserve and the Clean Development Mechanism that do not observe molecular CO₂ to calibrate financial products. Multinational policy applications such as the Paris Agreement and the United Nations Reducing Emissions from Deforestation and Degradation, constrained by Kyoto Protocol era processes, will benefit from NEE measurement avoiding unsupported claims of emission reduction, fraud, and forest conservation policy failure.