Estimation of Future Changes in Aboveground Forest Carbon Stock in Romania. A Prediction Based on Forest-Cover Pattern Scenario

Machine learning-based prediction and assessment of recent dynamics of forest net primary productivity in Romania

While the analysis of spatio-temporal changes in the net primary productivity (NPP) of forests can provide critical information on carbon cycle and climate change, these ecological trends have remained unclear in many countries worldwide, including Romania. By using complex (satellite, forest and climate) data, many sophisticated (machine learning) algorithms and some widely applied (the Mann-Kendall test and Sen's slope estimator) statistical procedures, this study investigates, for the first time, recent forest NPP trends (1987-2018) that occurred in Romania, in relation to climate change that affected the country over the past decades. Following the modelling, mapping and assessment of NPP dynamics, results showed almost exclusively positive trends for this ecological parameter, which accounts for ∼99% of all forest NPP changes that occurred throughout the country, after 1987. Interestingly, almost three quarters (∼73%) of all NPP increasing trends are statistically significant, which indicates that Romania's forests have recently experienced a large-scale improvement in carbon fluxes and stocks. Investigations of eco-climatic relationships suggest that climate change has partially contributed to these surprising NPP dynamics observed in recent decades. All these findings can provide valuable information for forest management and for many stakeholders and policymakers who operate in the forestry and climate fields in Romania.

Which Are the Best Site and Stand Conditions for Silver Fir (Abies alba Mill.) Located in the Carpathian Mountains?

Silver fir (Abies alba Mill.) is one of the most valuable and productive tree species across European mountains, that accomplish multiple economic, protective and ecologic functions. Alongside spruce (Picea abies (L.) Karst) and beech (Fagus sylvatica L.), silver fir is a characteristic species for the Romanian Carpathians. Although silver fir tree is recommended for the diversification of forests in order to increase the resistance to climate change, it is very sensitive to climatic excesses, especially those that proceed rapidly. Therefore, the aim of this study is to investigate both the environmental conditions and stand characteristics of fir from five mountain ranges of the Romanian Carpathians. The study is based on data recorded over a period of 10 years (1990–2000). As such, a total of 77,251 stands that occupy 211,954 hectares have been investigated in regard to silver fir behaviour. MATLAB scripts were used for analysing consistent data volumes as well as the impact of eight factors on the silver fir productivity (altitude, field aspect, field slope, soil type, participation percentage, road distance, structure and consistency). Our analysis has revealed that higher silver fir productivity is found at altitudes of up to 1200 m, on mid and upper slopes, on NW field aspects, on eutric cambisols and dystric cambisols, with a 10–20% participation in stand composition and in relatively-even aged stands with a full consistency. This study offers valuable insights for forest managers that require comprehensive information in adopting effective strategies to enhance forest resilience under climate change.

Contribution of Community-Managed Sal-Based Forest in Climate Change Adaptation and Mitigation: A Case from Nepal

Forests are viable tools in combating the impacts of climate change, as they are capable of sequestering atmospheric carbon and storing it in different pools. This study aimed to examine the carbon sequestration potential of community-managed Shorea robusta (Sal) forest and assess the practices that have the potential to reduce adverse climate change impacts, thereby improving the livelihoods of forest-based communities. For this, we obtained forest inventory-derived carbon data from 11 sample plots of Shorea robusta (Sal) forest, analyzed them using allometric equations, and estimated the carbon storage and climate change mitigation potential of these forests, while focus group discussions and desk review of secondary information were employed to investigate the adaptation potential. The results show that the estimated biomass density of the selected forest is 352.46 ± 63.79 t/ha, whereas the carbon stock density is 165.66 ± 29.98 t/ha and the CO2 equivalent is 598.07 ± 110.48 t/ha. The study further revealed that community forest management, as a successful model of participatory forest management and community forest user group (CFUG) as a resourceful local institution, has been playing an important role in the diversification of livelihoods and income opportunities, social cohesion and thus climate change adaptation through collective actions. The adaptation and mitigation of climate change impacts have been prioritized in the operational plans of the CFUGs. Through the promotion and prioritization of alternative energy, agroforestry and enhanced livelihood options, the CFUGs are committed to the sustainable management of forest resources and to enhancing the livelihoods of local communities. This study indicates the relevance of community forests as a priority institution for the implementation of Local Adaptation Plans for Action (LAPA) and support National Adaptation Program of Action (NAPA) to combat climatic impacts, providing important information for planners and policy makers in Nepal and elsewhere.

Assessment of Carbon Stock in Forest Biomass and Emission Reduction Potential in Malaysia

Malaysia has a large extent of forest cover that plays a crucial role in storing biomass carbon and enhancing carbon sink (carbon sequestration) and reducing atmospheric greenhouse gas emissions, which helps to reduce the negative impacts of global climate change. This article estimates the economic value of forest carbon stock and carbon value per hectare of forested area based on the price of removing per ton CO2eq in USD from 1990 to 2050. The economic value of biomass carbon stored in the forests is estimated at nearly USD 51 billion in 2020 and approximately USD 41 billion in 2050, whereas carbon value per hectare forest area is estimated at USD 2885 in 2020 and USD 2388 in 2050. If the BAU scenario of forest loss (converting forests to other land use) continues, the projected estimation of carbon stock and its economic value might fall until 2050 unless further initiatives on proper planning of forest management and ambitious policy implementation are taken. Instead, Malaysia’s CO2 emission growth started to fall after 2010 due to rising forest carbon sink of 282 million tons between 2011 and 2016, indicating a huge potential of Malaysian forests for future climate change mitigation. The estimated and projected value of carbon stock in Malaysian forest biomass, annual growth of forest carbon, forest carbon density and carbon sink would be useful for the better understanding of enhancing carbon sink by avoiding deforestation, sustainable forest management, forest conservation and protection, accurate reporting of national carbon inventories and policy-making decisions. The findings of this study could also be useful in meeting emission reduction targets and policy implementation related to climate change mitigation in Malaysia.

Utilizing the Available Open-Source Remotely Sensed Data in Assessing the Wildfire Ignition and Spread Capacities of Vegetated Surfaces in Romania

We bring a practical and comprehensive GIS-based framework to utilize freely available remotely sensed datasets to assess wildfire ignition probability and spreading capacities of vegetated landscapes. The study area consists of the country-level scale of the Romanian territory, characterized by a diversity of vegetated landscapes threatened by climate change. We utilize the Wildfire Ignition Probability/Wildfire Spreading Capacity Index (WIPI/WSCI). WIPI/WSCI models rely on a multi-criteria data mining procedure assessing the study area’s social, environmental, geophysical, and fuel properties based on open access remotely sensed data. We utilized the Receiver Operating Characteristic (ROC) analysis to weigh each indexing criterion’s impact factor and assess the model’s overall sensitivity. Introducing ROC analysis at an earlier stage of the workflow elevated the final Area Under the Curve (AUC) of WIPI from 0.705 to 0.778 and WSCI from 0.586 to 0.802. The modeling results enable discussion on the vulnerability of protected areas and the exposure of man-made structures to wildfire risk. Our study shows that within the wildland–urban interface of Bucharest’s metropolitan area, there is a remarkable building stock of healthcare, residential and educational functions, which are significantly exposed and vulnerable to wildfire spreading risk.