Forest Research Institute

About: Forest Research Institute is a facility organization based out in Dehra Dūn, India. It is known for research contribution in the topics: Population & Forest management. The organization has 5320 authors who have published 7625 publications receiving 185876 citations.

A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping

Abstract: Flash flood is a typical natural hazard that occurs within a short time with high flow velocities and is difficult to predict. In this study, we propose and validate a new soft computing approach that is an integration of an Extreme Learning Machine (ELM) and a Particle Swarm Optimization (PSO), named as PSO-ELM, for the spatial prediction of flash floods. The ELM is used to generate the initial flood model, whereas the PSO was employed to optimize the model. A high frequency tropical typhoon area at Northwest of Vietnam was selected as a case study. In this regard, a geospatial database for the study area was constructed with 654 flash flood locations and 12 influencing factors (elevation, slope, aspect, curvature, toposhade, topographic wetness index, stream power index, stream density, NDVI, soil type, lithology, and rainfall). The model performance was validated using several evaluators such as kappa statistics, root-mean-square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and area under the ROC curve (AUC-ROC) and compared to three state-of-the-art machine learning techniques, including multilayer perceptron neural networks, support vector machine, and C4.5 decision tree. The results revealed that the PSO-ELM model has high prediction performance (kappa statistics = 0.801, RMSE = 0.281; MAE = 0.079, R2 = 0.829, AUC-ROC = 0.954) and successfully outperformed the three machine learning models. We conclude that the proposed model is a new tool for the prediction of flash flood susceptibility at high frequency tropical typhoon areas.

Structural diversity promotes productivity of mixed, uneven-aged forests in southwestern Germany

Abstract: Forest diversity-productivity relationships have been intensively investigated in recent decades. However, few studies have considered the interplay between species and structural diversity in driving productivity. We analyzed these factors using data from 52 permanent plots in southwestern Germany with more than 53,000 repeated tree measurements. We used basal area increment as a proxy for productivity and hypothesized that: (1) structural diversity would increase tree and stand productivity, (2) diversity-productivity relationships would be weaker for species diversity than for structural diversity, and (3) species diversity would also indirectly impact stand productivity via changes in size structure. We measured diversity using distance-independent indices. We fitted separate linear mixed-effects models for fir, spruce and beech at the tree level, whereas at the stand level we pooled all available data. We tested our third hypothesis using structural equation modeling. Structural and species diversity acted as direct and independent drivers of stand productivity, with structural diversity being a slightly better predictor. Structural diversity, but not species diversity, had a significant, albeit asymmetric, effect on tree productivity. The functioning of structurally diverse, mixed forests is influenced by both structural and species diversity. These sources of trait diversity contribute to increased vertical stratification and crown plasticity, which in turn diminish competitive interferences and lead to more densely packed canopies per unit area. Our research highlights the positive effects of species diversity and structural diversity on forest productivity and ecosystem dynamics.

Environmental effects of aluminium.

Abstract: Aluminium (Al), when present in high concentrations, has for long been recognised as a toxic agent to aquatic freshwater organisms,i.e. downstream industrial point sources of Al-rich process water. Today the environmental effects of aluminium are mainly a result of acidic precipitation; acidification of catchments leads to increased Al- concentrations in soil solution and freshwaters. Large parts of both the aquatic and terrestrial ecosystems are affected.

Characterization of the structure, dynamics, and productivity of mixed-species stands: review and perspectives

Abstract: The growth and yield of mixed-species stands has become an important topic of research since there are certain advantages of this type of forest as regards functions and services. However, the concepts and methods used to characterize mixed stands need to be understood, as well as harmonized and standardized. In this review we have compiled a set of measures, indices, and methods at stand level to characterize the structure, dynamics, and productivity of mixed stands, and we discuss the pros and cons of their application in growth and yield studies. Parameters for the characterization of mixed stand structure such as stand density, species composition, horizontal (intermingling) and vertical tree distribution pattern, tree size distribution, and age composition are described, detailing the potential as well as the constraints of these parameters for understanding resource capture, use, and efficiency in mixed stands. Furthermore, a set of stand-level parameters was evaluated to characterize the dynamics of mixed stands, e.g. height growth and space partitioning, self- and alien-thinning, and growth partitioning among trees. The deviations and changes in the behaviour of the analysed parameters in comparison with pure stand conditions due to inter-specific interactions are of particular interest. As regards stand productivity, we reviewed site productivity indices, the growth–density relationship in mixed stands as well as methods to compare productivity in mixed versus monospecific stands. Finally, we discuss the main problems associated with the methodology such as up-scaling from tree to stand level as well as the relevance of standardized measures and methods for improving forest growth and yield research in mixed stands. The main challenges are also outlined, especially the need for qualitatively sound data.

Fuel characteristics of short rotation forest biomass

Abstract: Fuel characteristics of biomass from 12 tree species grown under a short rotation forestry regime were analysed. E. globulus, E. nitens and A. dealbata had the biggest trees while A. glutinosa, P. tomentosa and S. matsudana × alba 1002 had the smallest trees when the trees were harvested at the age of 3, 4 and 5 years. Higher heating value (HHV) ranged from 19.6–20.5 MJ/kg for wood, 17.4–20.6 MJ/kg for bark, and 19.5–24.1 MJ/kg for leaves, with the highest values for wood and bark being obtained from Pinus radiata . Wood basic density ranged from 250–500 kg/m 3 ; ash content, 0.7–1.4%; volatile matter content, 91.5–95.1%; fixed carbon content, 4.2–7.3%; and extractives content, 3.3–11.9%. Wood properties were significantly different from those of bark, and also different from those of leaves. Except basic density and the proportion of bark on the stem, properties of wood did not vary with either cutting age or stocking density. Wood from coppice crops did not differ from that of single stem, first harvest crops. Differences in tree size for species planted at similar plant populations determine species yields. Variations in properties between species and between tree parts have implications for feedstock handling, transport, drying, storage, and on the design of conversion systems.