Forest Management Strategies Research Articles

Quantifying the resistance of mixed-forests against natural hazards in the Pyrenees

Mountain protection forests can prevent natural hazards by reducing their onset and propagation probabilities. In fact, individual trees act as natural barriers against hydrogeomorphic events. However, assessing the structural strength of trees against these hazards is challenging, especially in a context of climate change due to the intensification of extreme events and changes in forest dynamics. Here, we focus on the mechanical analyses of two of the most common tree species across the Pyrenees (Abies alba Mill. and Fagus sylvatica L.) growing in two different areas (Spain and France), and affected by recurrent snow avalanche and rockfall events. We first performed 53 pulling test on mature trees, where the root-plate stiffness and the modulus of elasticity of the stems were evaluated. To further analyse the impact of forest management and climate on protective forests, we yielded information on tree growth using dendroecology techniques. Then, we assessed structure and neighbourhood characteristics for each target tree to account for the surrounding forest structure. Finally, using linear and structured equation models we tested if the mechanical capacity of the trees is determined either by functional traits (e.g. species, tree growth, diameter and height) or forest structural traits (e.g. tree density, tree structure and slenderness) or both. Our results suggest that the forest neighbourhood influences tree mechanical capacity through two pathways, including both functional and structural traits. The individual stiffness parameter of trees is influenced by their functional traits, while their structural traits are more closely related with changes in the modulus of elasticity. Both species exhibit varying levels of dominance in different locations, which is related to their resilience to the diverse natural hazards they confront. Our findings provide relevant insights to anticipating management strategies for forests that serve as a protective barrier against natural hazards in the context of a changing climate.

Soil solution chemistry weak response to long-term N addition points towards a strong resilience of northeastern American forests to past and future N deposition

Northern temperate and boreal forests are large biomes playing crucial ecological and environmental roles, such as carbon sequestration. Despite being generally remote, these forests were exposed to anthropogenic nitrogen (N) deposition over the last two centuries and may still experience elevated N deposition as human activities expand towards high latitudes. However, the impacts of long-term high N deposition on these N-limited forest ecosystems remain unclear. For 18 years, we simulated N deposition by chronically adding ammonium nitrate at rates of 3 (LN treatment) and 10 (HN treatment) times the ambient N deposition estimated at the beginning of the experiment at a temperate sugar maple and a boreal balsam fir forest site, both located in northeastern America. LN and HN treatments corresponded respectively to addition of 26 kgN·ha−1·yr−1 and 85 kgN·ha−1·yr−1 at the temperate site and 17 kgN·ha−1·yr−1 and 57 kgN·ha−1·yr−1 at the boreal site. Between 2002 and 2018, soil solution was collected weekly during summer and concentrations of NO3−, NH4+, Ca2+ and pH were measured, totalling ~12,700–13,500 observations per variable on the study period. N treatments caused soil solution NO3−, NH4+ and Ca2+ concentrations to increase while reducing its pH. However, ion responses manifested through punctual high concentration events (predominantly on the HN plots) that were very rare and leached N quantity was extremely low at both sites. Therefore, N addition corresponding to 54 years (LN treatment) and 180 years (HN treatment) of accelerated ambient N deposition had overall small impacts on soil solution chemistry. Our results indicate an important N retention of northeastern American forests and an unexpected strong resilience of their soil solution chemistry to long-term simulated N deposition, potentially explained by the widespread N-limitation in high latitude ecosystems. This finding can help predict the future productivity of N-limited forests and improve forest management strategies in northeastern America.

Influence of Government Policy, Community Ecological Awareness, and Adoption of New Technology on Successful Forest Management in Kalimantan

Forest management is a critical concern in Kalimantan, Indonesia, where rapid deforestation and ecological degradation pose significant environmental challenges. This study explores the influence of government policy, community ecological awareness, and new technology adoption on successful forest management. Utilizing a quantitative research design, data were collected from 170 respondents, including government officials, community leaders, and forest management professionals. Structural Equation Modeling (SEM) using Partial Least Squares (PLS) was employed for data analysis. The findings reveal that government policy, community ecological awareness, and new technology adoption significantly impact forest management success. Government policy emerged as the most influential factor, followed by new technology adoption and community ecological awareness. These results underscore the importance of an integrated approach that combines robust policies, active community engagement, and advanced technologies to enhance forest management outcomes. The study provides valuable insights for policymakers, practitioners, and researchers in developing effective strategies for sustainable forest management in Kalimantan and similar regions.

Soil methane emissions from plain poplar (Populus spp.) plantations with contrasting soil textures

The forest soil methane (CH4) flux exhibits high spatiotemporal variability. Understanding these variations and their driving factors is crucial for accurately assessing the forest CH4 budget. In this study, we monitored the diurnal and seasonal variations in soil CH4 fluxes in two poplar (Populus spp.) plantations (Sihong and Dongtai) with different soil textures using the static chamber-based method. The results showed that the annual average soil CH4 flux in the Sihong and Dongtai poplar plantations was 4.27 ± 1.37 kg CH4-C ha–1 yr–1 and 1.92 ± 1.07 kg CH4-C ha–1 yr–1, respectively. Both plantations exhibited net CH4 emissions during the growing season, with only weak CH4 absorption (–0.01 to –0.007 mg m–2 h–1) during the non-growing season. Notably, there was a significant difference in soil CH4 flux between the clay loam of the Sihong poplar plantation and the sandy loam of the Dongtai poplar plantation. From August to December 2019 and from July to August and November 2020, the soil CH4 flux in the Sihong poplar plantation was significantly higher than in the Dongtai poplar plantation. Moreover, the soil CH4 flux significantly increased with rising soil temperature and soil water content. Diurnally, the soil CH4 flux followed a unimodal variation pattern at different growing stages of poplars, with peaks occurring at noon and in the afternoon. However, the soil CH4 flux did not exhibit a consistent seasonal pattern across different years, likely due to substantial variations in precipitation and soil water content. Overall, our study emphasizes the need for a comprehensive understanding of the spatiotemporal variations in forest soil CH4 flux with different soil textures. This understanding is vital for developing reasonable forest management strategies and reducing uncertainties in the global CH4 budget.

Forest restoration effects on soil preferential flow in the paleo-periglacial eastern liaoning mountainous regions, China

To provide a practical reference index for the protection of water conservation forests and the establishment of vegetation in different forest restoration areas, we seek to clarify the preferential flow development and its influencing factors under different rainfall events in the forest restoration areas of paleo-periglacial landform in eastern Liaoning Province of China. To quantify the preferential flow development (PFI) in soil profile-scale through soil profile indexes, we carried out dual-tracer experiments with dyeing in two types of forest restoration lands (plantation forest, PF, and natural secondary forest, NSF) in the paleo-periglacial landform forestland to obtain the soil water infiltration trajectories and water-solute transport characteristics. The indexes of preferential flow morphology and pathway diversity (solute migration) were integrated to construct a more complete evaluation system of the PFI. In addition, we explored factors affecting the PFI through soil physical properties and root characteristics. The results showed that: (1) There were obvious preferential flows in both PF and NSF. Compared with NSF, preferential flow in PF diverged earlier, had greater non-equilibrium degree, more paths and higher development degree, and preferential flow was the main infiltration form. (2) Changes in infiltration amount played a key role in altering the PFI, i.e., increasing infiltration amount reduced the PFI, especially in PF (p < 0.05); (3) After water infiltration, the solute Br− diffusion range of the soil profile was wider than that of Brilliant Blue tracer, thus the development of preferential flow was better synthetical reflected by the indexes of water flow morphology and solute distribution characteristics; (4) Differences in the PFI can be explained by variations in clay content, total porosity (TP), and root volume density (RVD), with total path coefficients of 0.824, 0.462, and 0.624, respectively. In addition to establishing different forest restoration types in similar areas, it would be worthwhile to strengthen the prevention and control measures of soil and water loss in NSF, and properly manage PF in a near-natural model to enhance ecologically sustainable development of forest land. The results of this study contribute to the understanding of the hydrological processes of forest ecosystems in paleo-periglacial landforms, and provide theoretical support for the proposed forest management strategies.

Pollinator effectiveness and pollination dependency of bilberry (Vaccinium myrtillus) in Swedish hemi-boreal forests

Intensification of forest management to increase production of biomass has resulted in considerable habitat degradation with negative impacts on insect biodiversity, including beneficial insect groups such as pollinators. Yet, little is known about how reliant forest understory plants, such as bilberry (Vaccinium myrtillus), are on insect pollinators for reproduction. Here, we quantified the structure of the bilberry flower visitor community, compared the pollination effectiveness of the most common pollinators, and experimentally quantified bilberry pollination dependency. The bilberry pollinator community was comprised of several bee and hoverfly taxa. Bumblebees were the most important pollinators due to their high abundance and pollination effectiveness. Other bees, in particular, Andrena spp., and to a smaller extent, hoverflies, were also effective pollinators. Furthermore, bilberry was strongly pollen-limited, with only 40% of open-pollinated flowers setting fruit. Bilberry supports a diverse flower visitor community within hemi-boreal forests, for which it is highly dependent for reproduction. Given the ecological and cultural value of bilberry, the importance of insect pollinators for understory plants should be considered within forest management strategies.

Impact of Toumeyella parvicornis outbreak in Pinus pinea L. forest of Southern Italy: First detection using a dendrochronological, isotopic and remote sensing analysis

Climate change is expected to affect forests' growth and functioning and to increase their vulnerability to stressors such as prolonged drought and pest outbreaks. Identifying vulnerable forest stands and predicting tree decline is critical for timely management interventions to preserve forests integrity and associated ecosystem services. This study combined dendrochronological and isotopic analyses with satellite remote sensing to detect early warning signs of forest decline in a Pinus pinea L. stand in southern Italy affected by one of the first outbreak of the pine parasite Toumeyella parvicornis reported in Italy. Furthermore, through a comparative study of the analysis techniques, this research aimed to identify the most effective data processing strategies for detecting tree dieback of this species. Satellite analysis revealed a gradual decline in vegetation indices (NDVI, EVI, EVI2) of the stand from 2015 onwards, which coincided with the onset of defoliation due to the pest outbreak. The decline in defoliation intensified in 2020, leading to a severe tree carbon deficit and subsequent mortality of the pine stand in 2023. In comparison, indices such as EVI and EVI2 have been shown to be more sensitive than NDVI in detecting changes in canopy cover. The inclusion of the NDMI index provided important information on the moisture dynamics of the stand. Dendrochronological analyses complemented remote sensing data: a strong decrease in growth was observed from 2020 onwards, undemanding a tipping point for the Pinus pinea stand, which led to tree mortality in 2023. The study highlighted the higher sensitivity of detrended chronologies such as BAI and TRW-I in detecting signs of forest dieback compared to raw tree-ring data. Moreover, intrinsic water use efficiency (WUEi) analysis provided insight into the eco-physiological dynamics underlying pine tree decline, revealing lower tree water retention induced by defoliation. Finally, correlations between growth and WUEi data with meteorological variables highlighted how defoliation increased the vulnerability of trees to the effects of climate, influencing their ability to recover after the pest attack. In conclusion, the combination of these analysis methods provided a detailed and comprehensive overview of tree species dieback due to new invasive pest. Our findings providing valuable insights into the eco-physiological dynamics and early detection of signs of tree decline, useful for planning effective forest management strategies to counteract the diffusion of Toumeyella parvicornis across Italy and Europe.

Tree species mixing effects on the radial growth of Pinus massoniana and Castanopsis hystrix: A comparison between even-aged and uneven-aged stands

The establishment of mixed-species forests with complex structures and high biodiversity has emerged as a key approach for enhancing productivity and maintaining the stability of plantation forests. However, how the mixing effect changes with stand development and climate variation is still unclear. Additionally, little is known about how the mixing effects vary between even- and uneven-aged mixed planting strategies based on the same species combinations and site conditions. In this study, we used dendrochronological methods to reconstruct 37 years of annual growth series for even-aged mixed plantations (EMs) and uneven-aged mixed plantations (UEMs) of Pinus massoniana and Castanopsis hystrix, as well as their respective monocultures at the individual tree (286 trees in total) level. We found that in EMs, the growth of P. massoniana and C. hystrix was 20.8 % lower and 26.2 % higher than those of their monocultures, respectively. However, the growth of P. massoniana remained unchanged during the first 17 years of mixing, after which it was significantly suppressed by C. hystrix. The growth of P. massoniana and C. hystrix in the UEMs was 20.8 % and 26.2 % lower than that in their monocultures, respectively. Remarkably, the mixing effect on the growth of P. massoniana shifted from suppression to promotion after 30 years of mixing. Furthermore, the relative growth of P. massoniana in the UEMs increased with dry season precipitation. These results indicate that transforming pure plantations into uneven-aged mixed plantations may be a crucial forest management strategy for enhancing tree growth and to improving adaptation to future precipitation pattern changes. However, in EMs, thinning should be conducted before fast-growing, shade-intolerant species experience intense light competition.

Soil-based assessment of site productivity for southern pine plantations in the coastal plain of the southeastern US: (I) loblolly pine

Site productivity and forest management strategies hinge on intrinsic site resources such as soil water and nutrient availability. In this study, regression tree model and linear regression model approaches were employed to quantify the relationship between site index and soil parameters for loblolly pine plantations in the Coastal Plain. Both the optimal regression tree model and the final linear regression model identified modified CRIFF (Cooperative Research in Forest Fertilization) soil groups and surface soil extractable phosphorus (Mehlich 1 P) as significant variables for predicting site index. The final linear regression model, with a R2 of 0.899 and an RMSE of 1.12 m, exhibited superior performance compared to the optimal regression tree model. Additionally, mean annual increments in stand volume and green weight for each soil group were simulated and compared with data from a long-term loblolly pine culture/density experimental study in the same region. These resulting predictive models offer applicability across diverse sites and are particularly well-suited for areas where forest stands are not currently established.

Silver Fir (Abies alba Mill.): Review of Ecological Insights, Forest Management Strategies, and Climate Change’s Impact on European Forests

Silver Fir (Abies alba Mill.): Review of Ecological Insights, Forest Management Strategies, and Climate Change’s Impact on European Forests

Investigating the effects of climate change and anthropogenic activities on SOC storage and cumulative CO2 emissions in forest soils across altitudinal gradients using the century model

This study investigated the impact of climate change, grazing, manure application, and liming on soil organic carbon (SOC) stock and cumulative carbon dioxide (CO2) emissions in forest soils across different altitudes. Despite similar soil texture, acidity, and salinity across elevations, SOC stock significantly increased with altitude due to cooler temperatures and higher precipitation. The highest SOC stock (97.46 t ha−1) was observed at 2000–2500 m, compared to the lowest (44.23 t ha−1) at 500–1000 m. The Century C Model accurately predicted SOC stock, with correlation and determination coefficients exceeding 0.98. A climate change scenario projecting decreased precipitation (2.15 mm per decade) and increased temperature (0.4 °C) revealed potential SOC stock losses ranging from 28.36 to 36.35 %, particularly at higher altitudes. Grazing further decreased SOC stock, with a more pronounced effect at higher elevations. However, manure application (40 t ha−1 every four years) and liming (7–10 t ha−1 every three years) had positive effects on SOC stock, again amplified at higher altitudes and with an increase in lime application rate. In scenarios combining climate change with manure application and climate change with liming, manure application and liming mitigated some negative impacts of climate change, but could not fully offset them, resulting in 1.49–5.42 % and 0.39–4.07 % decreases respectively. Simulations of cumulative CO2 emissions mirrored the distribution of SOC stock, with higher emissions observed at higher altitudes and with management practices that increased SOC stock. This study emphasizes the critical role of conserving high-altitude forest soils and implementing optimal forest management strategies to combat climate change by minimizing SOC losses.

Contextualizing sustainable forest management and social justice in community-based forest management (CBFM) program in the Philippines

The Philippines' Community-Based Forest Management (CBFM) Program is the primary strategy for sustainable forest management and social justice in the uplands. The upland communities provided a catalytic role to restore degraded forestlands and protect the remaining forest cover in the country, but unlike the timber license agreement (TLA) concessionaires, they do not have enough assets to fulfill their needs and responsibilities. They are also subjected to restrictive policies beyond their capacity to follow. While numerous works of literature have been written on the successes and failures of different modes of community forestry in Asia and the Pacific for the past two decades, very limited, if any, attention has been given to the role of community welfare as a prerequisite for sustainability and social justice in forestry. Using the data on national CBFM assessment in the Philippines, this paper critically examines the CBFM Program after more than two decades of implementation using the community welfare lens. Thematic analysis of results revealed that in achieving sustainability and social justice in forestry, the following crucial elements should be taken into account: (1) land tenure is a crucial aspect of community welfare but the complexity of social-ecological relations must be taken into account; (2) skewed priority towards biophysical targets undermines the importance of socio-economic needs and considerations in the uplands; and (3) restrictive and conflicting policies significantly diminishes the potential of CBFM for transformative change.

Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach.

SummaryThe understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species‐specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness‐of‐fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested‐grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well‐differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests.

Local Community Attitude towards Forest-Based Ecotourism Development in Arbegona and Nensebo Woredas, Southern Ethiopia

Understanding local community awareness and attitude towards forest-based ecotourism welfare is an important input for policymakers to develop and implement sustainable forest resource management strategies. However, the local community’s awareness and attitude towards forest-based ecotourism development have been poorly assessed and documented in remote areas. To this end, the present study assessed the local community’s awareness and attitude in Arbegona and Nensebo woredas’ forests, southern Ethiopia, towards ecotourism development. Household and key informant interviews and focus group discussions were used to collect data. Results indicated that more than half (57.9%) of the respondents expressed a negative attitude towards forest-based ecotourism development. The educational status of the respondents, their age, presence of conservation measures, source of energy for household consumption, and biophysical and socio-cultural variations in the study sites are significantly associated with local communities’ attitudes that have been exhibited towards the development of ecotourism and conservation of forest resources. Creating awareness through persuasion and communication of new and well-suited information, promoting alternative livelihood options, encouraging local benefits from the conservation of forest resources, and compensating costs induced by wild animals can minimise negative attitudes, thereby contributing to the enhancement of local communities’ positive attitudes towards forest resource conservation.

Plant trait approach to assess the vulnerability of Rhododendron arboreum in western Himalayas

Climate change is profoundly impacting Himalayan ecosystems, with substantial challenges to keystone species like Rhododendron arboreum. Present study attempted to investigate R. arboreum response to varying environmental conditions at altitudes between 1500 and 3000 m in three western Himalayan temperate forests, through evaluating plant functional traits. IPCC's internal vulnerability framework, characterised by two dimensions: sensitivity and adaptive capacity was applied. Structural Equation Modelling (SEM) was applied to elucidate the relationship between traits and the dimensions. Sensitivity was analysed using sub components like Light Harvesting, Nutrient and Gas Fluxes, while adaptive capacity by Resource Efficiency, Architecture and Defence, Resource Limitation and Resource Facilitation. The results revealed high sensitivity (0.64) in moru oak forests, high adaptive capacity in moist temperate deciduous forests (0.59), and high vulnerability in ban oak forests (0.54). SEM Models for sensitivity and adaptive capacity were significant. Sensitivity exhibited positively significant influence of Nutrient and Gas Fluxes with path coefficient of 1.07 and 0.80, respectively. Adaptive capacity showed a positive relationship with the Resource Limitation and Architecture and Defence, while a negative relationship with Resource Facilitation, with a path coefficient of 0.94, 0.42 and −0.11, respectively. Overall, the vulnerability of R. arboreum to environmental changes is shaped by a complex interplay of physical characteristics (morphological), biological functions (physiological), and interactions with surroundings (ecological). These insights underscore the importance of understanding trait vulnerability dynamics for effective forest management strategies amidst changing environmental conditions.

Impact of Parthenium hysterophorus L. on floristic diversity in Dhauladhar foothills of Himachal Pradesh.

Parthenium hysterophorus L. has become a weed of global concern owing to its fast expansion and invasive character. In order to study the status of this noxious weed and its impact on floristic diversity in Dhauladhar foothills, the study was conducted during the year 2021-2022 in culturable wastelands of Dhauladhar ranges in Kangra district of Himachal Pradesh, India. The impact of Parthenium hysterophorus L. on associated species at different altitudes and aspects was observed. Our observations depicted that Parthenium hysterophorus L. has been growing more vigorously in the northern aspect than the southern aspect with the density of 37.78m-2 and 21.62m-2, respectively. The highest density of this noxious weed was recorded in the altitudinal range of 600-1200m (34.32m-2) while it was not observed beyond 1805m above sea level. The invasion of Parthenium hysterophorus L. significantly affected the plant density of other species. The descending order of the species as per dominance was observed as Cynodon dactylon, Trifolium repens, Oxalis latifolia, Parthenium hysterophorus L., and Ageratum houstonianum. The average number of species and species density were observed more in non-invaded sites (9.35 and 27.67m-2) than in invaded sites (7.10 and 20.60m-2). Species abundance and plant cover were observed more in non-invaded sites (28.73 and 657.90 m2ha-1) than in invaded sites (22.70 and 322.30 m2ha-1). Species diversity, richness, and evenness were reported to decline in invaded sites (1.56, 0.95, and 0.81, respectively) with respect to the non-invaded sites (1.94, 1.16, and 0.88, respectively). The study highlights the significant concerns associated with the invasive weed within the plant communities. Understanding its invasive status holds considerable implications for local afforestation initiatives, forest management strategies, and conservation policies. Furthermore, this investigation lays a foundational groundwork for implementing effective measures to get rid of this alien weed.

Adaptive silviculture for climate change in the Great Lakes- St. Lawrence Forest Region of Canada: Background and design of a long-term experiment

We present the implementation of the Adaptive Silviculture for Climate Change (ASCC) initiative at the Petawawa Research Forest (PRF) in Ontario, Canada. The study addresses the urgent need for adaptive forest management strategies in response to climate change by examining silvicultural treatments aimed at mitigating its impacts on forest ecosystems. It addresses the complex interplay between climate change projections, regional climate characteristics, and forest management practices for pine dominated forests in the Great Lakes-St. Lawrence Forest region of Canada, underscoring the importance of adaptive approaches in sustaining forest ecosystems. We outline the design and objectives of five distinct treatments—control, business-as-usual, resistance, resilience, and transition—implemented over 4 replicate blocks on a 212-ha area at the PRF. We provide detailed descriptions of each treatment’s management objectives, desired future conditions, and silvicultural strategies. We conclude by summarizing planned research efforts, including seedling survival assessments, phenological monitoring, and measuring treatment impact on fuel loads. By addressing the challenges and opportunities of climate change as part of an international research network, this research will contribute to a deeper understanding of forest ecosystem responses to climate change and inform adaptive management strategies for sustainable forest management.

Multitemporal Dynamics of Fuels in Forest Systems Present in the Colombian Orinoco River Basin Forests

In Colombia’s Orinoco, wildfires have a profound impact on ecosystem dynamics, particularly affecting savannas and forest–savanna transitions. Human activities have disrupted the natural fire regime, leading to increased wildfire frequency due to changes in land use, deforestation, and climate change. Despite extensive research on fire monitoring and prediction, the quantification of fuel accumulation, a critical factor in fire incidence, remains inadequately explored. This study addresses this gap by quantifying dead organic material (detritus) accumulation and identifying influencing factors. Using Brown transects across forests with varying fire intensities, we assessed fuel loads and characterized variables related to detritus accumulation over time. Employing factor analysis, principal components analysis, and a generalized linear mixed model, we determined the effects of various factors. Our findings reveal significant variations in biomass accumulation patterns influenced by factors such as thickness, wet and dry mass, density, gravity, porosity, and moisture content. Additionally, a decrease in fuel load over time was attributed to increased precipitation from three La Niña events. These insights enable more accurate fire predictions and inform targeted forest management strategies for fire prevention and mitigation, thereby enhancing our understanding of fire ecology in the Orinoco basin and guiding effective conservation practices.

Quantifying soil erosion and soil organic carbon conservation services in indian forests: A RUSLE-SDR and GIS-based assessment

Indian forests, having sixteen types of vegetation, provide various ecosystem services. Forests reduce water erosion of soil, reduce floods and conserve low river flow during dry seasons. Present study estimated annual sedimentation, texture, soil organic carbon control service of forests of India using the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) approach through GIS technique along with identifying important drivers responsible for erosion in forests. The soil erosion control service was based on five factors viz., rainfall erosivity, soil erodibility, slope, crop management, conservation practice factor and SDR across the various forest dominated river basins. Geo-detector modelling was performed to evaluate environmental drivers responsible for soil erosion. Valuation of soil control service of the India’s forests was estimated based on damage and replacement cost method. Annual soil loss rate was maximum in Tropical Thorn Forest and in Ganga River basin. Maximum sediment control and SOC conservation against the soil erosion control service by India’ forests were due to Tropical Dry Deciduous Forest with a total annual sedimentation control and SOC conservation of 33,056,560 tonnes and 3,31,115.06 tonnes, respectively. The conservative estimate of the economic value of soil conservation service by the forests of India was US$ 535.6 M with an average of 4.40 US$ ha−1 and a maximum share of value for Tropical Dry Deciduous Forest i.e. 294.18 million US$ and average maximum value for Littoral and Swamp Forest (28.91 US$ ha−1). The soil erosion in Tropical and Sub-tropical Forest was influenced by the interactive effects between NDVI and Bulk Density. In contrast, soil erosion in the temperate and alpine area was influenced by anthropogenic activity in combination with climatic factors. Present study accounts the role of India’s forests for the soil conservation service and may provide inputs to implement forest and reservoir management strategies besides providing information for Integrated Watershed management and Catchment Treatment Plans.

Exploring forest fire susceptibility and management strategies in Western Himalaya: Integrating ensemble machine learning and explainable AI for accurate prediction and comprehensive analysis

Forest fires pose a significant threat to ecosystems and socio-economic activities, necessitating the development of accurate predictive models for effective management and mitigation. In this study, we present a novel machine learning approach combined with Explainable Artificial Intelligence (XAI) techniques to predict forest fire susceptibility in Nainital district. Our innovative methodology integrates several robust models — AdaBoost, Gradient Boosting Machine (GBM), XGBoost and Random Forest — with a Deep Neural Network (DNN) as a meta-model in a stacking framework. This approach not only utilises the individual strengths of these models, but also improves the overall prediction performance and reliability. By using XAI techniques, in particular SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations), we improve the interpretability of the models and provide insights into the decision-making processes. Our results show the effectiveness of the ensemble model in categorising forest fire susceptibility into different zones: very low, low, moderate, high and very high. In particular, the stacking ensemble and XGBoost models identified extensive areas of high and very high susceptibility, with precision, recall and F1 values underpinning their effectiveness. These models achieved ROC AUC values above 0.90, with XGBoost performing exceptionally well with an AUC of 0.94. The precision, recall and F1 values for these models are remarkably high. The inclusion of confidence intervals for the most important metrics in all models emphasises their robustness and reliability and supports their practical use in forest fire management. Through SHAP summary plots, we analyze the global variable importance, revealing annual rainfall and Evapotranspiration (ET) as key factors influencing susceptibility. Local analysis using LIME consistently highlights the importance of annual rainfall, ET, and distance from roads across all models. This study fills an important research gap by providing a comprehensive and interpretable modelling approach that improves our ability to predict and effectively manage forest fire risk and is consistent with environmental protection and sustainable development goals.