Management Of Forest Resources Research Articles

Economic valuation of selected ecosystem services in Islamabad Capital Territory (ICT), Pakistan.

Payment for ecosystem services (PES) is a mechanism where a consumer is able and ready to pay for the protection of the precise ecosystem service and there must be a provider such as local societies receiving an economic resource, who in return, must have the ability to maintain that ecosystem service. Economic valuation provides basis for payment for ecosystem services. Therefore, objective of this study was to evaluate tourism and carbon stock services of the Islamabad Capital Territory (ICT), Pakistan. Two forest zones (Chirpine and Scrub) of Islamabad capital territory (ICT) were selected for estimation of carbon stock and their carbon credits and carbon worth, a questionnaire-based survey was conducted for tourism as a payment for ecosystem services. The method for carbon stock assessment was systematic sampling for Chirpine forest whereas random sampling was done for scrub forest. The size of sampling plot was 17.84 m radius, and a total of 93 plots (49 Scrub zone and 44 Chirpine zone) was taken in the study area. The carbon stock of both zones (Chirpine and Scrub zone) is 22556.75 ton/ha (Chirpine 20105.79, Scrub 2450.96) and total carbon dioxide sequestered by both zone is 82557.72 ton/ha (Chirpine 73587.2, Scrub 8970.52), total carbon credits of both zone is 302160.87 (Chirpine 269328.97, Scrub 32831.9) and the carbon worth of both Chirpine and scrub zone is 4532418.92 $ (Chirpine 4039937.09$, Scrub 492481.83$). Similarly, from tourism point of view, in Shakar Parian, 94% tourists were agreed for PES whereas 6% were disagreed for the PES (the 6% tourist were disagreed to contribute for PES, 40% were agreed for Rs.5 contribution and 54% for Rs.10.). moreover, in Lake view Park, 97% tourists were agreed and 3% are disagreed (In Lake View Park 5% tourists were disagreed for the PES contribution whereas 32% were agreed for Rs.5 and 63% were for Rs.10). In Damen e Koh, around 87% tourist were agreed and 13% were disagreed, (24% were agreed for the contribution of Rs.5 and 63% tourists were agreed for the contribution of Rs.10). In Marghazar Zoo, 93% tourists were agreed (22% were agreed for contribution of Rs.5 and 71% tourist were agreed for contribution of Rs.10) and 7% are disagreed for PES whereas 7% tourists were not agreed for contribution. PES may implement to compensate forest and parks manager to ensure better management of the forests and parks. Due to prime location and scenic beauty of the ICT, it has huge potential for implementation of PES mechanism for sustainable forest management and conservation. Therefore, it is recommended that Capital Development Authority (CDA) Islamabad should devise a plan for implementation of PES in forests and parks of ICT for its sustainable management of recreational and forest resources.

ЛІСОВІ РЕСУРСИ ЯК ЧАСТИНА ЕКОНОМІЧНОГО ПОТЕНЦІАЛУ КРАЇНИ

Forests are extremely important for the planet ecosystem and perform a number of ecological functions: they provide oxygen, regulate the climate, protect the soil from erosion, regulate water flows and contribute to the purification of the natural environment, and they are a habitat for numerous living creatures. But besides, forestry is characterized as a significant part of the country's economy. The purpose of the article is to study the role of forest resources in the economic potential of the national economy, to identify the current state and problems of forestry in Ukraine. In the work the attention is paid to the influence of forest resources on logging, hunting, various branches of the wood processing manufacturing, on food, pharmaceutical, energy, and tourism industries, as well as on science, education, and culture. Among other things, the infrastructural, export and international potential of forest ecosystems is highlighted. It is emphasized that irresponsible forest use can lead to catastrophic environmental consequences, including floods, landslides, destruction of buildings and disruption of the balance of ecosystems, etc. For this reason, it is justified that the forestry industry requires a rational and careful approach, as well as compliance with the principles of sustainable forestry. The article lists the pre-war problems of forestry: imperfect distribution of management functions, complications in property rights realization, high level of corruption and illegal activities in forests, shortage of relevant specialists in the field, deterioration of the sanitary condition of forests, lack of incentives for the introduction of nature-saving technologies, etc. A special place is given to the assessment of the impact of a full-scale war on forestry: the occupation of large forest areas, soil and water pollution, a significant increase in the number of fires, mining of territories, illegal felling of trees, stoppage of hunting activities, damage to forest infrastructure, inability to carry out normal forest protection activities, etc. It was concluded that all these problems have an extremely negative impact on the state of Ukraine's forest resources, but the final assessment of damage to forest ecosystems can be established after surveys, which will actually be conducted only after the end of the war. But despite the war, forestry is trying to continue fulfilling its obligations to the national economy and society. Therefore, state, public and international support, implementation of effective management of forest resources are an extremely important tasks in modern conditions.

Satellite Remote Sensing and Geographic Information System Technologies for Industrial Tree Plantation Mapping and Monitoring: A Way Forward for the Sustainable Development of the Philippine ITP Industry

KEY POINTS
 ● Industrial Tree Plantations (ITPs) are a vital contributor to the Philippines' log and timber production, but these ITPs requires better and more efficient way of characterization and monitoring.
 ● Current policies require ground validations surveys to monitor ITPs for regulation purposes. However, these approaches are often difficult to conduct, time consuming and expensive.
 ● Satellite remote sensing (SRS) and Geographic Information System (GIS) technologies offer an efficient alternative to traditional ground surveys for mapping and monitoring ITPs.
 ● SRS and GIS enable detailed mapping of ITPs, including species-level identification, and provides valuable data for forest resource management and environmental monitoring.
 ● SRS and GIS technologies should be integrated into existing policies by the Department of Environment and Natural Resources (DENR) to efficiently map, monitor, and manage ITPs in the country, ensuring informed decision-making and sustainable forestry practices.

Development of Semantic-Web Based Forest Resources Database

There are some forest resources (such as Trees, Shrubs, and Water bodies) in the university main campus. These resources are used for various purposes ranging from teaching, researches medicinal and domestic purposes and among many others. However, there is no record of official documentation on them. Thus, this study aims to provide a semantic-web based database system for efficient management of forest resources. We adopted the W3C semantic web framework in the design and development of this work. Specifically, we focused on the layers 1 to 5 of the framework. The layers include; Resource Description Framework (RDF), Web Ontology Language (OWL), Extensible Markup Language (XML), User Interface). The Uschold’s and Kings’ method was applied in creating the ontology. The implementation process was carried out by populating the database with the Taxonomies of the Trees on University of Energy and Natural Resources (U.E.N.R) campus by means of creating an Ontology File using protégé. Some of the basic information that we provided by the proposed semantic web database include trees, their scientific name, geographical coordinate, physical location, medicinal value and other important data. We performed alpha test by involving six senior forest science students who used the application, evaluated it and came out with a good result which is shown in the chapter four of this documentation.

Eucalyptus Species Discrimination Using Hyperspectral Sensor Data and Machine Learning

The identification of tree species is very useful for the management and monitoring of forest resources. When paired with machine learning (ML) algorithms, species identification based on spectral bands from a hyperspectral sensor can contribute to developing technologies that enable accurate forest inventories to be completed efficiently, reducing labor and time. This is the first study to evaluate the effectiveness of classification of five eucalyptus species (E. camaldulensis, Corymbia citriodora, E. saligna, E. grandis, and E. urophyla) using hyperspectral images and machine learning. Spectral readings were taken from 200 leaves of each species and divided into three dataset sizes: one set containing 50 samples per species, a second with 100 samples per species, and a third set with 200 samples per species. The ML algorithms tested were multilayer perceptron artificial neural network (ANN), decision trees (J48 and REPTree algorithms), and random forest (RF). As a control, a conventional approach by logistic regression (LR) was used. Eucalyptus species were classified by ML algorithms using a randomized stratified cross-validation with 10 folds. After obtaining the percentage of correct classification (CC) and F-measure accuracy metrics, the means were grouped by the Scott–Knott test at 5% probability. Our findings revealed the existence of distinct spectral curves between the species, with the differences being more marked from the 700 nm range onwards. The most accurate ML algorithm for identifying eucalyptus species was ANN. There was no statistical difference for CC between the three dataset sizes. Therefore, it was determined that 50 leaves would be sufficient to accurately differentiate the eucalyptus species evaluated. Our study represents an important scientific advance for forest inventories and breeding programs with applications in both forest plantations and native forest areas as it proposes a fast, accurate, and large-scale species-level classification approach.

Social Forestry for Community Wellfare and the Forest Sustainability

This article analyzes the Indonesian goverments program for the welfare of all Indonesian people, based on forest resource management, namely the social forestry program. In the concept of living as a state, the implementation of the social forestry program must bring the maximum benefit to the welfare of the community, in this case the community around the forest and also to the sustainability of the forest. The writing of this article uses a qualitative method by taking the research location in the jurisdiction of KPH Cianjur, BKPH Cianjur, KPH Puncak. The results showed that the social forestry program was very important to implement although there werestill some problems that needed to be corrected in practice in the field so that the social forestry program would bring the greatest benefit to the village community around the forest and the sustainability of the forest it self.Kata Kunci : perhutanan social, kesejahteraan masyarakat, kelestarian hutan

Combining Digital Imaging and Artificial Neural Networks for Individual Volumetric Estimation of Non-Straight Trees

Tree volume models have become an important decision-making tool in forest resources management. The objective of this work was to create Artificial Neural Networks (ANN) to fit individual tree models from the Brazilian Savanna (the Cerrado biome), characterized by non-straight and very bifurcated tree stems. Data were collected in two different areas and through different methods: i) individual tree volume by digital photographs, and also by tree climbing measurements (both obtained in a non-destructive way); ii) tree volumes measured destructively by the traditional rigorous cubing procedure after thinning. Data obtained from climbing measurements were compared with the corresponding tree obtained from digital photographs, resulting in a reasonable operational linear relation of 0.80. Ten ANN structures were created with different combinations of forestry variables. Five ANN structures depicted predictive ability results above 0.80. Then, the results obtained by ANN were compared with those obtained by classic tree volumetric models, once again showing the predictive superiority of ANN. The present study indicates that tree volume obtained from digital photographs, achieved by popular mobiles, can be safely used for the estimation of very-crooked trees from the Brazilian Savanna and demonstrated the greater predictive ability of ANN in relation to the classic regression-based volumetric models in terms of lower modeling bias.

The Impact of Technological Dynamics and Fiscal Decentralization on Forest Resource Efficiency in China: The Mediating Role of Digital Economy

This study explores the multi-dimensional relationships between technology, fiscal decentralization, and forest resource efficiency, and the pivotal role played by the digital economy as a mediator in 2002–2020. First, this study evaluates the Chinese provinces’ forest resource efficiency using multi-dimensional inputs and outputs of forest sectors. Further, we use two sorts of technology: high-technology expenditure and forest technology education. Fiscal decentralization in terms of local government expenditure on forest resources makes the study innovative and richer in analysis. A SBM-DEA analysis showed that the Anhui, Beijing, Jiangsu, Shanghai, and Zhejiang provinces have the highest efficiency scores, implying very efficient forest resource management. Subsequently, the robust econometric estimator Driscoll and Kraay is applied. The study’s findings disclose that both dimensions of technology increase the Chinese provinces’ forest resource efficiency through technological expenditure and forest technology education. Fiscal decentralization towards forest resource management expenditure increases the efficiency of forests. Urbanization and economic development reduce the efficiency of forests. The digital economy can effectively help to improve the efficiency of forest resources. The presence of moderating effects reveals that the influence of the digital economy on forest resource efficiency is positive when it is coupled with economic development, fiscal decentralization, technology, and urbanization.

Future possibilities for long-term business cooperation between private forest owners and forest service providers in Slovenia

Abstract Private forest ownership, with small and fragmented forest properties prevailing in Europe, is affected by demographic, economic and social changes as well as by forest-related policy goals. This is reflected in the lack of knowledge about forest management, insufficient forest management and underutilization of forest resources. Considering that, business cooperation between private forest owners and with forest service providers or managers is recognized as one of the key instruments to increase the efficiency of private forest management. The aim of this study is to investigate whether there is a potential for further development of forest lease as form of long-term business cooperation. In this research, interviews (n=8) were conducted with tenants who have signed long-term forest lease contracts with private forest owners in Slovenia. The results show that there are limited possibilities for further development of long-term business cooperation between private forest owners and forest service providers/managers (e.g. forest lease). The results indicate that there are many benefits of long-term business cooperation for both sides, but private forest owners’ interest is questionable. If we want long-term business cooperation (forest lease) to succeed, forest lease should be recognized in legislation, education about business cooperation (forest lease) should be given to public forest service employees, so they could promote forest lease and provide information to private forest owners. In addition, a connection between potential business partners should be established and examples of good practice should be promoted to gain trust between business partners, which could increase private forest owners’ interest and consequently improve private forest management and utilization of forest resources from private forests.

Chromosome-scale genomes of commercially important mahoganies, Swietenia macrophylla and Khaya senegalensis

Mahogany species (family Meliaceae) are highly valued for their aesthetic and durable wood. Despite their economic and ecological importance, genomic resources for mahogany species are limited, hindering genetic improvement and conservation efforts. Here we perform chromosome-scale genome assemblies of two commercially important mahogany species: Swietenia macrophylla and Khaya senegalensis. By combining 10X sequencing and Hi-C data, we assemble high-quality genomes of 274.49 Mb (S. macrophylla) and 406.50 Mb (K. senegalensis), with scaffold N50 lengths of 8.51 Mb and 7.85 Mb, respectively. A total of 99.38% and 98.05% of the assembled sequences are anchored to 28 pseudo-chromosomes in S. macrophylla and K. senegalensis, respectively. We predict 34,129 and 31,908 protein-coding genes in S. macrophylla and K. senegalensis, respectively, of which 97.44% and 98.49% are functionally annotated. The chromosome-scale genome assemblies of these mahogany species could serve as a vital genetic resource, especially in understanding the properties of non-model woody plants. These high-quality genomes could support the development of molecular markers for breeding programs, conservation efforts, and the sustainable management of these valuable forest resources.

An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China

ABSTRACT Large-scale forest composition mapping and change monitoring are essential for regional and national forest resource management, monitoring, and carbon stock assessment. However, the existing large-scale mapping methods are not effective enough in terms of efficiency and accuracy. To address this limitation, this study proposes a lightweight one-dimensional convolutional neural network (LW-CNN) model for forest composition mapping. The LW-CNN model is developed using Landsat imagery covering 470,700 km2 obtained from Google Earth Engine (GEE) collected during two periods (2007 and 2018). The proposed LW-CNN is compared with a visual geometry group with 16 convolutional layers (VGG16), a residual network with 34 convolutional layers (Resnet34), and a residual network with 50 convolutional layers (Resnet50) in terms of model accuracy and efficiency. The factors influencing forest composition change are analyzed using the structural equation model (SEM). The results show that the proposed LW-CNN model can outperform the other three models in terms of model accuracy, achieving a mean overall accuracy (OA) of: 0.75 and efficiency of 7–22-fold. The changed forest composition from 2007 to 2018 accounts for 29.6% of the total forest area. The SEM results show that the climate factors have the most significant effect on the forest composition change. This study presents an innovative model for large-scale forest composition mapping, which is proven to be both efficient and accurate. This study also provides insights into the factors that affect the forest composition change, which could be valuable for forest resource management, monitoring, and carbon stock assessment.

How to adequately determine the top height of forest stands based on airborne laser scanning point clouds?

Top height (TH) is one of the most important features of forest stands that is used in forest resource management. Thus far, the TH has been mainly determined in forestry on the basis of field measurements. There are certain accepted theoretical guidelines on how the TH should be determined. However, due to high cost and time consumption, it is difficult to meet these assumptions with traditional field measurement methods. Currently, remote sensing is widely used in forest inventory, also for the determination of TH. However, it is still usually conducted by linking the remote sensing data—most often airborne laser scanning (ALS) point clouds—with ground-based measurements using the area-based approach. Different plot sizes and point cloud metrics are used to determine TH, making it difficult to compare the results. There is therefore a need for a universal methodology for determining TH directly from ALS data – one that is consistent with the methodology used for field measurement data. This paper presents the results of an experiment that was aimed at assessing the accuracy of TH determination on the basis of ALS data. A comparison of the six considered ALS-derived proxies of TH showed that the individual tree detection approach was the most accurate. The bias of this method, when calculated for 48 artificial forest stands, amounted to 0.15 m. The approach based on the lower percentiles of the distribution of point heights significantly underestimated the TH from −0.67 m to up to −1.9 m. On the basis of the obtained results, we claim that TH can be determined, based on ALS data without ground measurements, with an accuracy that is acceptable for forest practitioners and researchers.

Fertility Variation and Gene Diversity in Forest Populations

Fertility variation, defined as a difference in the ability to create progeny (i.e., reproductive success) among individuals, was reviewed using the related available theoretical and practical literature in an attempt to contribute to and improve future studies on the subject. Fertility variation is a useful guide for various purposes such as gene conservation, seed production programs, forest genetic resource (i.e., seed sources) management, other forestry practices (e.g., regeneration), and evolutional and physiological studies. Many papers and proceedings have been published, including both theoretical and practical approaches, on how fertility variation has improved in the last two decades. Large variations in fertility were widely reported among populations within species and among species. We reviewed the literature and combined our diverse knowledge to examine fertility variations and their linkage parameters. Fertility variations and their related parameters (e.g., gene diversity, status number, effective parent number, parental–balance curves) estimated based on reproductive characteristics have been studied for many years using easy and cheap surveys that are used for different purposes in forest sciences. Their importance is increasing and their use is becoming more widespread because of these advantages, leading to improvements in research papers. While many research papers have recently been published on fertility variations and linkage parameters, a review paper has not been published to date. Therefore, a review paper is needed based on a literature survey and unpublished experience, as a guide for future studies.

Formation of the environmental and economic basis of the balanced development of the forest sector

The study is devoted to the study of the formation of the ecological and economic foundations of the balanced development of the forest sector. The work examines key aspects of the state of forestry, and also identifies factors affecting the economic and environmental sustainability of this sector. The article analyzes the current state of forestry, highlights the main environmental problems associated with the exploitation of forest resources, and also considers the possibilities of their rational use. In particular, the research is focused on the identification of optimal strategies for forest use, which would contribute to ensuring a balance between economic needs and preservation of the natural environment. An integrated approach to the management of forest resources is considered, taking into account economic, ecological and social aspects. The application of the latest technologies, the creation of ecological reclamation programs and support for the sustainable development of forestry are key components of the proposed strategies. Therefore, the article highlights the need and possible ways of forming ecological and economic foundations for the balanced development of the forest sector with a view to increasing the efficiency of the use of forest resources and preserving the ecological balance.

The interactive effect of endogenous and exogenous institutions on forest use practices in socio-culturally diverse landscapes of Cameroon

AbstractIn resource-dependent communities of sub-Saharan Africa, it is widely held that endogenous institutions either countervail or complement exogenous institutions, indicating inconsistency in empirical evidence. This has re-ignited interest to establish the independent and/or interactive effect of both endogenous and exogenous institutional structures. This paper quantitatively analyses the independent and interactive effects of community-based (endogenous) and state-based (exogenous) forest management institutions (FMIs) on the exploitation of forest resources, drawing from a representative sample of 446 households from three socio-culturally diverse landscapes of Cameroon. The paper introduces a multiplicative interaction term and used the heteroscedasticity-based instrumental variables approach to estimate the direct and indirect effects of exogenous and endogenous institutions on the behaviour of users of forest-based resources. The results indicate that: (i) Both exogenous structures of FMIs and the interaction term significantly constrain the extractive behaviour of forest resource users; (ii) endogenous structures and not rules are vital in improving the role of exogenous structures in forest resource management; (iii) while traditional rules are less significant in shaping forest resource exploitation, their effectiveness is highly significant across the study sites and (iv) institutional compatibility and complementarity was observed in landscapes that were formerly shaped by British colonial influence (Bakossi and Kilum-Ijim). This paper does not only establish the relative influence of exogenous and endogenous FMIs, it also highlights future research pathways on institutional change in the context of environmental resource management in sub-Saharan Africa.

Coupling of Forest Carbon Densities with Landscape Patterns and Climate Change in the Lesser Khingan Mountains, Northeast China

This research investigated the effects of the forest landscape composition and spatial distribution and local climate change’s lag effects on the carbon density of stands and provides a reference for optimizing the stand structure and sustainable management of forest resources in Xinqing District, Yichun City, Heilongjiang Province, China. Using second-class forest resource survey data of the Xinqing Forestry Bureau for 2007 and 2017, the forest carbon density, landscape pattern index and local forest climate were quantified by ArcGIS10.7, Fragstats4.2 and SPSS25, and a coupling coordination degree model was constructed to reflect their correlations. The overall broadleaved mixed forest area was larger in the new green area, and the overall forest productivity had improved in the past ten years. Forest management gradually improved from nonforest to forest land, resulting in a high degree of fragmentation in the surrounding landscape. The coupling research on the forest carbon density and the forest landscape pattern index and local climate index showed that, overall, the landscape pattern and the impact of climate change on the forest carbon density had a positive interaction; adjustments and improvements can be made to the forest carbon density in the poor-condition area by combining specific situations of the landscape pattern and climate change.

Utilizing Indigenous Knowledge Systems on Climate Change for Forestry Conservation in Kenya

Forest conservation is important in climate change mitigation. The Indigenous Knowledge (IK) or Indigenous Knowledge System (IKS) has recently been recognised in forest conservation for climate change mitigation. The potential use of IKS in climate change management in Sub-Saharan Africa including Kenya is unknown. Numerous analytical postulations detailing how to integrate IKS in climate change management have been formulated. However, this information is fragmented and mostly lost in sociology literature. This paper briefly reviews the indigenous knowledge related to different aspects of forest resource management. This review delves at in-depth information on the IKS and climate change management in Sub-Saharan Africa, emphasizing Kenya. For this review, the scooping review methodology was used to describe the state of knowledge and map the available evidence of the role of IKS for forest conservation and climate change adaptation. It discusses the role of IKS in climate change management in Sub-Saharan Africa and the potential application of the IKS in preventing adverse climate change effects. The integration of IKS to guide the climate change management have been evaluated and the threats to IKS and their conservation deliberated. It is generally observed that in many rural communities in Kenya, IKS is useful for enhanced food production, forest conservation and natural disaster management. But being culture-specific, IKS can be adopted across communities in SSA for real time management of climate change.

The Role of Local Government in Improving the Economy and Welfare of the Wamesa Great Tribes Society in West Papua, Through A Sustainable Forest Development Program: in the Perspective of Collaborative Governance in Public Service

The purpose of this study is to analyze and describe the role of local government in improving the economy and welfare of the Wamensa great tribal community in West Papua, through a sustainable customary forest development program in the perspective of Collaborative Governance in Public Service. Collaborative governance is an important process in the Indonesian government today. The government implements Collaborative governance by providing space for other actors to participate, such as the national private, foreign, and public. Collaborative management aims to reduce conflict, facilitate learning, and increase consensus among stakeholders. As a legal administrator, the government should work effectively and efficiently in providing good public services to all citizens. Currently, West Papua still has around 81% of sustainable forest remaining, with a wealth of various types of wild animals with ecosystems in it (mega-biodiversity). Local Government as key in making policies has impacts on improving the economy and people's welfare. This research used a qualitative method with a case study in the customary forest of the Wamesa great tribe in West Papua. The study results showed that there are 3 main indicators to support the success of the Government's role in sustainable forest development, such as; economic, social, and ecological. However, there is a governance Pillar in the paradigm of public administration to show the success of collaborative governance. It required collaborative governance management synergically between government and non-government actors. The aim is to consensus on adaptive solutions through forest resource management. They are concerned with economic, social, and ecological complexities, as a concrete form of the vision and mission of the Regional Government in providing public services, as a portfolio documentation of national development.

Forest Landscape Model Initialization with Remotely Sensed-Based Open-Source Databases in the Absence of Inventory Data

Forecasts of the forest ecosystem dynamics are important for environmental protection and forest resource management. Such forecasts can support decisions about where and how to restore damaged forests and plan felling, and in forest conservation. Forest landscape models (FLM) are used to predict changes in forests at the landscape level. FLM initialization usually requires detailed tree species and age data; so, in the absence of forest inventory data, it is extremely difficult to collect initial data for FLM. In our study, we propose a method for combining data from open sources, including remote sensing data, to solve the problem of the lack of initial data and describe initializing the LANDIS-II model. We collected land cover classification and above-ground biomass products, climate, soil, and elevation data to create initial vegetation and ecoregion maps. Our method is based on some simplifications of the study object—some tree species are replaced by groups of species; the forest stand is considered homogeneous. After initialization, the natural dynamics without harvesting and disturbances were simulated by the Biomass Succession extension for 200 years. The study presents a detailed methodology that can be used to initialize other study areas and other FLMs with a lack of field data.

Predicting vegetation dynamics in Deux Balé National Park, Burkina Faso, using land change modeler

In recent years, the natural vegetation of Burkina Faso has undergone unprecedented anthropisation. To date, most studies have focused only on diachronic analysis based on satellite imagery. Land use dynamics studies give an account of the past and present situation, but do not provide quantitative and qualitative information on the future of this vegetation. On the other hand, a prospective analysis of the dynamics would enable us to better assess the future of our forest ecosystems. Predictive data are essential for decision-making and implementing appropriate policy responses relating to sustainable forest resources management. The main objective of this study was to predict the vegetation dynamics of the Deux Balé National Park by modelling the year 2025. Thus, we selected the variables that best explained the anthropization process. A land change model was selected for the study. The model was calibrated using only variables with a V-Cramer coefficient greater than or equal to 0.1. This model is based on error budgeting and prediction. Visual and statistical comparisons of the simulated and actual 2016 maps allowed for better calibration of the model to simulate changes in the area of land-cover classes by 2025. The results revealed that, between 2016 and 2025, a significant regression of savanna vegetation will occur in favor of anthropized areas and gallery forests. Thus, from this period, gallery forests and anthropized areas covered up to 138 ha and 2914 ha, respectively. However, the savanna vegetation area decreased by 1186 ha, 961 ha, and 893 ha from 2016 to 2025, respectively. Therefore, urgent action must be taken to preserve the potential of the forest resources in parks.