Forest Management Initiatives Research Articles

Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region

Accurately estimating aboveground biomass (AGB) in forest ecosystems facilitates efficient resource management, carbon accounting, and conservation efforts. This study examines the relationship between predictors from Landsat-9 remote sensing data and several topographical features. While Landsat-9 provides reliable data crucial for long-term monitoring, it is part of a broader suite of available remote sensing technologies. We employ machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and Random Forest (RF), alongside linear regression techniques like Multiple Linear Regression (MLR). The primary objectives of this study encompass two key aspects. Firstly, the research methodically selects optimal predictor combinations from four distinct variable groups: Landsat-9 (L1) data, a fusion of Landsat-9 data and Vegetation-based indices (L2), and the integration of Landsat-9 data with the Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) (L3) and the combination of best predictors (L4) derived from L1, L2, and L3. Secondly, the research systematically assesses the effectiveness of different algorithms to identify the most precise method for establishing any potential relationship between field-measured AGB and predictor variables. Our study revealed that the Random Forest (RF) model was the most efficient method utilizing Landsat-9 OLI and SRTM DEM (L3) predictors, achieving remarkable accuracy. This conclusion was reached by assessing its outstanding performance when compared to an independent validation dataset. The RF model exhibited remarkable accuracy, presenting relative mean absolute error (RMAE), relative root mean square error (RRMSE), and R2 values of 14.33%, 22.23%, and 0.81, respectively. The XGBoost model is the subsequent choice with RMAE, RRMSE, and R2 values of 15.54%, 23.85%, and 0.77, respectively. The study further highlights the significance of specific spectral bands, notably B4 and B5 from Landsat 9 OLI data, in capturing spatial AGB distribution patterns. Integration of vegetation-based indices, including TNDVI, NDVI, RVI, and GNDVI, further refines AGB mapping precision. Elevation, slope, and the Topographic Wetness Index (TWI) are crucial proxies for representing biophysical and biological mechanisms impacting AGB. Through the utilization of openly accessible fine-resolution data and employing the RF algorithm, the research demonstrated promising outcomes in the identification of optimal predictor-algorithm combinations for forest AGB mapping. This comprehensive approach offers a valuable avenue for informed decision-making in forest management, carbon assessment, and ecological monitoring initiatives.

Modeling Forest Above-Ground Biomass of Teak (Tectona grandis L. F.) Using Field Measurement and Sentinel-2 Imagery

Over the last few decades, remote sensing has emerged as a dependable and cost-effective method for collecting precise data on forest biophysical parameters, aiding in sustainable forest management and global initiatives to combat climate change. This research aimed to develop a model for estimating the above-ground biomass (AGB) of Teak (Tectona grandis L. F.) by combining field measurements with Sentinel-2 earth observation data. The study took place in 36-year-old teak plantation areas within the Sagarnath Forest Development Project in Nepal’s Sarlahi district. Field measurements were conducted using a destructive systematic sampling method, employing 10 × 10 m2 sample plots, and the volume of logs was determined using Newton’s formula. A total of 30 sample plots were used for calibration, while 10 were utilized for validation purposes. The findings revealed that the average AGB per plot was 814 kg (equivalent to 81.4 t ha−1), with a minimum value of 716 kg (71.6 t ha−1) and a maximum value of 1,060 kg (106 t ha−1). The study utilized five independent variables, namely, the Red band, Green band, Blue band, near-infrared (NIR), and normalized difference vegetation index (NDVI) values from Sentinel-2 imagery data, to develop estimation models. Among the 12 models examined, model M10 proved to be the best fit for accurate AGB estimation (adjusted R2 = 0.9809, RMSE = 0.01269, AIC = −170, and p-value = < 8.39e−21). The equation of the best-fitted model was ln (AGB) = A + B × Red + C × Green + D × Blue2 + E × ln (NIR) + F × ln (NDVI), providing an accurate estimate of AGB. Model validation involved a t-test comparing the observed and calculated AGB values for ten sample plots, demonstrating no significant difference (p-value = 0.3662 > 0.05). This model has the potential to facilitate AGB biomass calculations and carbon stock estimates for teak plantations of similar age groups.

Combining LiDAR and Spaceborne Multispectral Data for Mapping Successional Forest Stages in Subtropical Forests

The Brazilian Atlantic Rainforest presents great diversity of flora and stand structures, making it difficult for traditional forest inventories to collect reliable and recurrent information to classify forest succession stages. In recent years, remote sensing data have been explored to save time and effort in classifying successional forest stages. However, there is a need to understand if any of these sensors stand out for this purpose. Here, we evaluate the use of multispectral satellite data from four different platforms (CBERS-4A, Landsat-8/OLI, PlanetScope, and Sentinel-2) and airborne light detection and ranging (LiDAR) to classify three forest succession stages in a subtropical ombrophilous mixed forest located in southern Brazil. Different features extracted from multispectral and LiDAR data, such as spectral bands, vegetation indices, texture features, and the canopy height model (CHM) and LiDAR intensity, were explored using two conventional machine learning methods such as random trees (RT) and support vector machine (SVM). The statistically based maximum likelihood (MLC) algorithm was also compared. The classification accuracy was evaluated by generating a confusion matrix and calculating the kappa index and standard deviation based on field measurements and unmanned aerial vehicle (UAV) data. Our results show that the kappa index ranged from 0.48 to 0.95, depending on the chosen dataset and method. The best result was obtained using the SVM algorithm associated with spectral bands, CHM, LiDAR intensity, and vegetation indices, regardless of the sensor. Datasets with Landsat-8 or Sentinel-2 information performed better results than other optical sensors, which may be due to the higher intraclass variability and less spectral bands in CBERS-4A and PlanetScope data. We found that the height information derived from airborne LiDAR and its intensity combined with the multispectral data increased the classification accuracy. However, the results were also satisfactory when using only multispectral data. These results highlight the potential of using freely available satellite information and open-source software to optimize forest inventories and monitoring, enabling a better understanding of forest structure and potentially supporting forest management initiatives and environmental licensing programs.

Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species

Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.

Assessing the potential of forest stands for edible mushrooms productivity as a subsistence ecosystem service in Ethiopia

Wild edible mushrooms are recognized as a fundamental component of forest management and rural development initiatives, offering farmers a substantial supplementary source of income. Thus, exploring the valuable wild mushrooms and modeling fungal fruiting in different forest systems in the tropics could provide additional insight into fungal responses to environmental factors and allow for better decision making related to forest management in the face of climate change. In many parts of the world, edible wild mushrooms are considered economically valuable non-timber forest products (NTFPs). In Ethiopia, forest management policies based on NTFPs are needed to make better use of these resources. A thorough assessment of wild mushroom as NTFPs that occur in Ethiopian forests and their uses is key to understanding what actions are needed to manage forests at the local level. We aimed (1) to record the fresh weight of edible wild mushrooms produced in natural and plantation forests in Ethiopia and (2) to develop models to predict sporocarp production in these two forest systems. We established 63 sample plots of 100 m2. All mature and young edible wild mushrooms were harvested weekly during the main rainy season to quantify their abundance and fresh weight. Composite soil samples collected from each plot and climate data recorded for each study area were used to develop models. In total, 64 edible fungal species were collected. The average annual total fresh weight production in plantations (2097.57 kg ha–1) was significantly greater than that produced in natural forests (731.18 kg ha–1). Six alternative models were fitted, and three yield categories were also defined as possible responses. Latitude, soil organic matter and minimum daily temperature were identified as relevant explanatory factors. Our yield classification models were fitted to predict the annual yields of edible fungi based on climate, soil and area-specific information in Ethiopia. The developed models should serve as a basis for further studies in Ethiopian forests to optimize forest management based on NTFPs, specifically edible wild mushrooms.

Simulating Sustainable Forest Management Practices Using Crown Attributes: Insights for Araucaria angustifolia Trees in Southern Brazil

Araucaria angustifolia (Bertol.) Kuntze, commonly known as Brazilian pine, is a significant tree species in the Brazilian flora that once covered an area of 200,000 km2 in the Southern region. During the 1970s, high-quality timber logs from this conifer became the primary export product of the country. However, the species is endangered due to uncontrolled exploitation and is subject to a harvesting ban. It is crucial, therefore, to explore sustainable cultivation methods for this species, which necessitates urgent research and scientific insights. In this study, we present a simulation of a management strategy for in situ conservation by manipulating growth space and crown size dynamics. Forest inventory data and mixed forest regression equations were employed to describe the horizontal dimensions of average and maximum potential crown growth, resulting in two management scenarios. The results presented in management diagrams show that both approaches required logging numerous trees to ensure adequate space for healthy tree growth and provide soil coverage and forest protection. Therefore, the absence of effective forest management initiatives for Araucaria forests may have further implications for the structure, production, conservation, and overall development. To address these challenges, we propose two hypotheses: firstly, that tree diameter depends on crown dimensions, which are in turn influenced by tree growth space, and, secondly, that crown dimensions serve as a reliable indicator of existing competition and can be utilized to simulate forest management practices. We urge that implementing sustainable forest management initiatives for Araucaria angustifolia at selected locations can contribute to expanding natural forest areas, mitigate deterioration caused by high competition, discourage illegal logging, and prevent overexploitation of their edible seeds, which hinders regeneration. Our results underscore the significant implications of the lack of forest management initiatives in rural properties, potentially resulting in irreversible deterioration. The exact consequences of this deterioration remain unclear, emphasizing the need for further studies to understand its eventual effects on the growth reaction of trees of different diameters, ages, and crown conditions after the liberation of their crowns.

Challenging the dominant path of forest policy? Bottom-up, citizen forest management initiatives in a top-down governance context in Poland

Forest governance in Poland is characterised by the dominance of public forest ownership and hierarchical, top-down policy-making. These governance arrangements, characteristic of post-socialist countries, have traditionally been challenged by environmental NGOs, advocating stronger protection of old-growths. Recently, institutional stability of the forest policy field has been increasingly influenced by numerous citizen initiatives responding to technocratic local forest management decisions. These initiatives, so far not analysed scientifically, vary in terms of the issues addressed, actions employed, and the local actors involved. In the paper we use a data base of 274 such initiatives to explore their manifestation, actors involved, main postulates, and the responses of forest managers. Based on this, we explored whether these initiatives pose challenges to the traditional forest management and, if so, what kind. We imply that the growth of bottom-up initiatives indicates a growing diversity of beliefs and values regarding forests and the increasing determination of local people to impact local environmental decisions. Furthermore, informed by the institutional theory, we argue that the growth of local initiatives, particularly during and after Covid-19 pandemics, suggests the eroding legitimacy of dominant rules and discourses. This process is particularly visible in sub-urban forests, which are increasingly seen through a ‘well-being discourse’ that highlights cultural, regulative and supportive functions of forests, while putting less emphasis on provisioning functions. We also identify a networking trend among the initiatives that unifies their discursive background and enhances their influence at the national level. Therefore, local activists can be seen as a new advocacy group in the Polish forest policy subsystem. In response to local demands public forest administration has introduced institutional changes enhancing participation but their impact is still to be assessed. We recommend establishing a monitoring programme to track new participatory practices and to identify and promote best practices.

Achieving Sustainable Development Goals in Ghana: The Contribution of Non-Timber Forest Products towards Economic Development in the Eastern Region

Globally, non-timber forest products (NTFPs) continue to contribute vastly to addressing the food, poverty reduction, income, and livelihood requirements of people in rural areas. However, as of now, there are no specific existing data highlighting the periodic contributions of NTFPs to the economy of the eastern region and the country. In Ghana, insufficient attention has been paid to the legislative and regulatory environments for the creation of NTFPs. Since forest policies continue to classify NTFPs as “minor” forest products, they receive less attention than wood in forest management initiatives and policies. The absence of a definitive policy on NTFPs has hampered their promotion, commercialization, and supply chain management. This study analyses the contribution of NTFPs towards economic development in the eastern region and the achievement of SDGs in Ghana. Through focus group discussions and a thematic analysis, it was concluded that NTFPs contribute immensely towards the economic development of the eastern region and the country through employment and direct taxes. Ultimately, it is evident from the study that the destruction of the Atiwa Forest Reserve for the purpose of bauxite mining will widely hinder the country’s achievement of its SDGs. Additionally, the study found that residents will continue to exploit forest resources if the core concerns of institutional deficiencies and rural poverty are not addressed. To curb this situation, there should be the sustainable, regulated, and authorized harvesting of NTFPs/NWFPs, community/user empowerment, and sectoral education and training programmes, etc. Even though these are common solutions, the study found them extremely rare within the study area.

Can We Predict Male Strobili Production in Araucaria angustifolia Trees with Dendrometric and Morphometric Attributes?

Knowledge of the formation and correlation of reproductive structures with dendro/morphometric variables of the Araucaria angustifolia tree species is a tool for its conservation and viability for sustainable forest management. We counted visually in araucaria trees the number of male strobili in RGB images acquired by Remotely Piloted Aircraft System (RPAs) over forest remnants. The diameter at the breast height (d), total height (h), crown radii (cr), crown base height (cbh), periodic annual increment in d based on increment rolls were measured, and the morphometric indices and crown efficiency were calculated with these variables. The relationships of these variables with male strobili production were analyzed by Pearson’s correlation and multivariate analysis techniques (cluster, factorial analysis, and main components). The morphometric variables correlated with the production of male strobili were d (r = 0.58, p-0.0002), crown diameter (r = 0.62, p < 0.0001), crown area (r = 0.62, p < 0.0001), coverage index (r = 0.51, p-0.001) and slenderness (r = −0.39, p-0.01). We argue that the production of male strobili is related to the vitality, dimension, density, growth space, and position in the stratum of the tree inside the forest, inferring a relationship between reproductive structures with the shape, size, growth space, and tree density. Such aspects shall be considered in future forest management initiatives in Southern Brazil.

Fusing multi-season UAS images with convolutional neural networks to map tree species in Amazonian forests

Remote sensing images obtained by unoccupied aircraft systems (UAS) across different seasons enabled capturing of species-specific phenological patterns of tropical trees. The application of UAS multi-season images to classify tropical tree species is still poorly understood. In this study, we used RGB images from different seasons obtained by a low-cost UAS and convolutional neural networks (CNNs) to map tree species in an Amazonian forest. Individual tree crowns (ITC) were outlined in the UAS images and identified to the species level using forest inventory data. The CNN model was trained with images obtained in February, May, August, and November. The classification accuracy in the rainy season (November and February) was higher than in the dry season (May and August). Fusing images from multiple seasons improved the average accuracy of tree species classification by up to 21.1 percentage points, reaching 90.5%. The CNN model can learn species-specific phenological characteristics that impact the classification accuracy, such as leaf fall in the dry season, which highlights its potential to discriminate species in various conditions. We produced high-quality individual tree crown maps of the species using a post-processing procedure. The combination of multi-season UAS images and CNNs has the potential to map tree species in the Amazon, providing valuable insights for forest management and conservation initiatives.

Community enforcement and tenure security: A fuzzy-set qualitative Comparative analysis of twelve community forest management initiatives in the Peruvian Amazon

The interest of policymakers in community management of tropical forests is ever growing. Yet, a large research body shows varied levels of success of community conservation initiatives. While policymakers often prioritize legal forest ownership, mostly land titles, consensus exists that success rather depends on a broader set of local institutional arrangements and their fit with the forest context. In this paper, we contribute to building theory on these institutional arrangements and their interaction. We apply a fuzzy set Qualitative Comparative Analysis to case study data on 12 voluntary community conservation initiatives in northern Peru to explore the relationship between local enforcement, legal and alternative property rights, and conservation effectiveness. As recommended for QCA our case selection was intentional and the cases exhibit diverse conservation successes, geographic characteristics, legal and customary property rights, and enforcement mechanisms. We conclude that strong community enforcement mechanisms are indispensable for effective conservation in voluntary initiatives. Furthermore, we find for cases with strong enforcement mechanisms, that some government back-up, i.e., local government support for enforcement and/or legal rights to conserve the forest, significantly increases conservation effectiveness. Strong conservation enforcement tends to be present in communities with strong forest rules, leaders, and pre-existing community institutions. Our findings suggest the importance of paying close attention to community characteristics during project design and refraining from one-size-fits-all-solutions, such as focusing mainly on the presence of legal ownership rights over the forest. Instead, more focus needs to be placed on understanding existing community institutions and supporting communities to strengthen and adapt these for conservation enforcement, rather than imposing new arrangements. Finally, policymakers can help community enforcement institutions become even more effective, by providing them with legal rights to conserve the forest and by strengthening their relationship with local governments so that they receive support in situations they struggle to handle alone.

Individual Tree Basal Area Increment Models for Brazilian Pine (Araucaria angustifolia) Using Artificial Neural Networks

This research aimed to develop statistical models to predict basal area increment (BAI) for Araucaria angustifolia using Artificial Neural Networks (ANNs). Tree species were measured for their biometric variables and identified at the species level. The data were subdivided into three groups: (1) intraspecific competition with A. angustifolia; (2) the first group of species that causes interspecific competition with A. angustifolia; and (3) the second group of species that causes interspecific competition with A. angustifolia. We calculated both the dependent and independent distance and the described competition indices, considering the impact of group stratification. Multi-layer Perceptron (MLP) ANN was structured for modeling. The main results were that: (i) the input variables size and competition were the most significant, allowing us to explain up to 77% of the A. angustifolia BAI variations; (ii) the spatialization of the competing trees contributed significantly to the representation of the competitive status; (iii) the separate variables for each competition group improved the performance of the models; and (iv) besides the intraspecific competition, the interspecific competition also proved to be important to consider. The ANN developed showed precision and generalization, suggesting it could describe the increment of a species common in native forests in Southern Brazil and with potential for upcoming forest management initiatives.

Responses of Indigenous People to the Climate Changes: A Case Study of the Surels of Dolakha District of Nepal

This paper has examined the way the Surels, an indigenous group inhabiting in Suri village of Dolakha district, perceive climate change and also has attempted to document their adaptive strategies to the changes brought about by climate change and global warming. These peoples have developed uniquely insightful ways of observing, interpreting, and responding to the impacts of climate changes through interacting and closely linking their lives with their surroundings. They clearly linked climate change with the changes in the weather patterns over the years indicating erratic rainfall patterns, advancing monsoon, advancing summer and spring, shorter and warmer winter, drier and hotter summer. This paper argues that these people observe and encounter climate and environmental changes immediately and use traditional knowledge and survival skills to adapt to these changes as they occurred. They have devised, though it is not well documented, useful coping mechanisms—modifying cropping pattern and crop types, community-based afforestation and forest management initiatives, improve water management, involvement of community organization in water management and seasonal migration to India- to respond and reduce climate induced risks and impacts which have enabled them to achieve stable livelihoods in their environment.

Diversity and Distribution of Forest Ants (Hymenoptera: Formicidae) in Nepal: Implications for Sustainable Forest Management.

Simple SummaryThere is little information available about the species diversity and distribution patterns of Nepalese ants, as well as their importance in maintaining forest health. A survey of forest ants was conducted in Nepal to learn about their diversity, distribution, and role in forest management. Ants were collected using vegetation beating, sweeping, and hand collection methods in eastern, central, and western Nepal. Seventy ant species from thirty-six genera and six subfamilies were recorded in the study. The research also discovered five genera and nine species new for the country, as well as eight tramp species, four of which are major ecological, agricultural, and/or household pests. The study discovered that western Nepal and the Siwalik region have a relatively high ant diversity. Ant diversity was found to decrease with increasing elevation. The assessment of ant diversity using multiple sampling methods that cover all seasons and forest types may be useful in obtaining complete ant diversity data. Early intervention through sustainable forest management initiatives would aid in preventing invasive ant incursions in the forests of Nepal.The information available on the diversity of ant species and their distribution and interaction with forest health in Nepal remains limited. As part of a nationwide project on forest health, we conducted inventories to assess the diversity and distribution of forest ants and their role in forest management in Nepal. Ants were collected from 187 plots of 10 m × 10 m size along the north–south belt transects in eastern, central, and western Nepal. We used vegetation beating, sweeping, and hand collection methods in selected forest types. In each transect, we designed six plots in each major forest type (Sal, Schima–Castanopsis, and broadleaf mixed forests) and three plots each in deodar, Alnus, riverine, and Cryptomeria forests. We recorded 70 ant species from 36 genera and six subfamilies. This includes five genera and nine species new for the country, as well as eight tramp species, four of which are major ecological, agricultural, and/or household pests. Our study indicates that forest ant species richness is high in western Nepal and the Siwaliks, and it decreases as elevation increases. The high diversity of ant species in the forests of Nepal needs to be assessed with further exploration using multiple sampling methods covering all seasons and forest types. Ants can be useful indicators for ecosystem management and human impacts on forests. Reports of invasive ants in Nepalese forests indicate the relevance of urgent interventions through sustainable forest management initiatives to prevent future incursions.

Analyzing canopy height variations in secondary tropical forests of Malaysia using NASA GEDI

Tropical forests play a significant role in regulating the average global atmospheric temperature encompassing 25 % of the carbon present in the terrestrial biosphere. However, the rapid change in climate, arising from unsustainable human practices, can significantly affect their carbon uptake capability in the future. For understanding these deviations, it is important to identify and quantify the large-scale canopy height variations arising from previous anthropogenic disturbances. With the advent of NASA GEDI spaceborne LiDAR (light detection and ranging), it is now possible to acquire three-dimensional vertical structural data of forests globally. In this study, we evaluate the applicability of GEDI for analyzing relative canopy height variations of secondary tropical forests of different age groups located across multiple geographical regions of peninsular Malaysia. The results for RH98 GEDI metric trends for the lowland and hill forests category across 4 different disturbance groups show a positive correlation between mean relative height and secondary forest ages. The consistency of these findings with previous studies in the region indicate the usefulness of GEDI to provide valuable insights into the patterns and drivers of forest height variation. Thus, this study contributes toward the operationalization of spaceborne LiDAR technology for monitoring forest disturbances and measuring biomass recovery rates and should help support large-scale sustainable forest management initiatives with respect to the tropical forests of Malaysia.

Cognitive Maps Reveal Diverse Perceptions of How Prescribed Fire Affects Forests and Communities

The potential for prescribed fire to address fuel management and forest restoration goals has received considerable attention. However, many wildfire risk mitigation practitioners and researchers consider prescribed fire to be an underutilized tool for forest and fire management. Prescribed fire can affect a broad range of values (e.g., air quality, wildlife habitat, timber, protection of homes) and these effects, which we term valued outcomes, may result from complex dynamics operating within fire-prone social-ecological systems. Increasing the effective use of prescribed fire requires a better understanding of how these dynamics are perceived by stakeholders, whose support is crucial for forest and fire management initiatives that affect diverse groups of people. We evaluated perceptions of the effects of prescribed fire on valued outcomes using data from 111 cognitive maps elicited from stakeholders in the wildfire-prone Eastern Cascades Ecoregion of central Oregon. As representations of relationships among biological, physical, social, political, and other factors that structure individuals’ understanding of a system, cognitive maps are ideal for analyzing perceptions of dynamics in complex social-ecological systems. We found that prescribed fire was perceived to positively affect valued outcomes in individuals’ cognitive maps. However, when we aggregated individuals’ cognitive maps to evaluate perceptions of prescribed fire at varying stakeholder group sizes, we found that perception of desirable effects declined with group size. Additionally, representatives of fire response and non-governmental organizations tended to perceive prescribed fire more favorably, while private citizens and representatives of private businesses emphasized adverse effects. Finally, we measured how the perceptions of the effects of prescribed fire varied across 15 distinct valued outcomes and found that air quality, aesthetic values, and wildlife habitat were perceived to be most negatively affected by prescribed fire, while cultural and historical values, protection of flora, water quality, and firefighter safety were perceived to be most positively affected. Taken together, our results help to explain the challenge of scaling up the use of prescribed fire and highlight the need for policy processes that account for stakeholders’ views of the multiple—and potentially opposing—effects of prescribed fire on different valued outcomes.

Evaluating forest resilience to global threats using functional response traits and network properties.

Ecosystem functions provided by forests are threatened by direct and indirect effects of global change drivers such as climate warming land-use change, biological invasions, and shifting natural disturbance regimes. To develop resilience-based forest management, new tools and methods are needed to quantitatively estimate forest resilience to management and future natural disturbances. We propose a multidimensional evaluation of ecological resilience based on species functional response traits (e.g., functional response diversity and functional redundancy) and network properties of forested patches (e.g., connectivity, modularity, and centrality). Using a fragmented rural landscape in temperate south-eastern Canada as a reference landscape, we apply our multidimensional approach to evaluate two alternative management strategies at three levels of intensity: (1) functional enrichment of current forest patches and (2) multi-species plantations in previously non-forested patches. Within each management strategy, planted species are selected to maximize functional diversity, drought tolerance, or pest resistance. We further compare how ecological resilience under these alternative management strategies responds to three simulated disturbances: drought, pest outbreak, and timber harvesting. We found that both management strategies enhance resilience at the landscape scale by increasing functional response diversity and connectivity. Specifically, when the less functionally diverse patches are prioritized for management, functional enrichment is more effective than the establishment of new multi-species plantations in increasing resilience. In addition, randomly allocated multi-species plantations increased connectivity more than those allocated in riparian areas. Our results show that across various management strategies, planting species to enhance biodiversity led to the highest increase in functional response diversity while planting pest-resistant species led to the highest increase in landscape connectivity. Planting biodiversity-enhancing species (i.e., species that maximize functional diversity) mitigated drought effects equally well as planting with drought-tolerant species. Our multidimensional approach facilitates the characterization at the landscape scale of forest resilience to disturbances using both functional diversity and network properties while accounting for the importance of response traits to future disturbances. The simulation approach we used can be applied to forest landscapes across different biomes for the evaluation and comparison of forest management initiatives to enhance resilience.

Assessment of a pluralistic advisory system: the case of Madhupur Sal Forest in Bangladesh

ABSTRACTPurpose: Participatory forest management initiatives in Madhupur Sal Forest in Bangladesh are characterized by the coexistence of diverse types of advisory service providers. Despite a decade of implementation of forest management initiatives, an assessment of the service delivery from a pluralistic advisory service framework is not evident. Drawing on the framework of pluralistic advisory service this study aimed to assess the role and performance of different advisory service providers that contribute to the management of forest resources.Methodology: We employed a stakeholder analysis to identify different advisory service providers, along with their power relations with forest dwellers. Data were collected using a participatory workshop and nine interviews.Findings and practical implications: The study found that most of the advisory service providers did not ensure the quality of the services, and did not orient their services towards the needs and demands of the forest dwellers. The advisory service providers continued to work with a coordination gap among themselves and the forest dwellers, which ultimately hindered their collective efforts to mobilize resources and build the strong relational condition necessary for the proper management of forest resources.Theoretical implications: This study applied a ‘best fit’ framework to the micro-level case of a forest advisory service, which helped to explore the dynamics of an advisory system linked to forest management initiatives.Originality: This is the first attempt to assess a pluralistic advisory system for forest management in Bangladesh.

Silviculture for forest management in Nepal

Forests and trees have social, ecological and economic importance to humankind. It is high time to manage worlds’ forests sustainably to ensure supply of forest based goods and services and reduce the adverse impacts of climate change. This paper highlights the history and current status of forest management, challenges and opportunities, various approaches adopted in forest management and recent initiatives in sustainable and scientific forest management (SFM) in Nepal. About one-third of the total 6.61 million ha (45%) of Nepal’s forest has been handed over to over 30,000 forest user groups. Various failed attempts in forest management in the past were mainly due to lack of institutional capacity, political back-up, conflict, etc. “Forestry for Prosperity” - a new vision announced at the 10th National Conservation Day in 2012, re-introduced the concept of sustainable and scientific forest management and launched this in ten districts with designated program and budget in the same year. Accordingly, forest blocks are identified, inventoried, management plans drawn and implemented. Over 69, 000 ha forests in 11 districts are under silviculture management to date. Thus managed forests show profuse regeneration, improved supply of forest products, increased revenue, improved forest health and enhanced capacity of forestry professionals. Yet, lack of political and professional commitment, inadequate human and financial resources, and weak institutional and professional competency are specific challenges to SFM in Nepal. Creating enabling environment, institutional reorganization, enhancing forest management capacity, improved forestry governance, reducing non-forestry workload of government forestry staff, and preparation and use of standard silvicultural operational guidelines have been suggested to upscale SFM in Nepal. Banko JanakariA Journal of Forestry Information for Nepal Special Issue No. 4, 2018, Page : 15-20

Towards active utilisation of community forestry: Silvo-institutional model for sustainable forest management in Nepal

This paper explains what we term the ‘silvo-institutional model’ for a more productive, sustainable and equitable management of community forests in Nepal. The paper draws on four years of action research in six research sites of Kavre and Lamjung districts, complemented by the review of silviculture-based forest management by Government of Nepal in various parts of the country. The findings indicate that first, early silviculture-based forest management initiatives have failed because they did not adequately consider the policy and institutional dimensions. Second, current initiatives, while looked promising for the active utilisation of community forests, have faced with complex regulatory and institutional barriers. We argue that a new ‘silvoinstitutional model’, which combines technological and institutional dimensions, has a potential to increase the prospect of successful implementation of silviculture-based forest management.Banko JanakariA Journal of Forestry Information for NepalSpecial Issue No. 4, 2018, Page: 120-129