Showing papers by "Forest Research Institute published in 2019"

Global distribution of earthworm diversity

Abstract: Soil organisms, including earthworms, are a key component of terrestrial ecosystems. However, little is known about their diversity, their distribution, and the threats affecting them. We compiled a global dataset of sampled earthworm communities from 6928 sites in 57 countries as a basis for predicting patterns in earthworm diversity, abundance, and biomass. We found that local species richness and abundance typically peaked at higher latitudes, displaying patterns opposite to those observed in aboveground organisms. However, high species dissimilarity across tropical locations may cause diversity across the entirety of the tropics to be higher than elsewhere. Climate variables were found to be more important in shaping earthworm communities than soil properties or habitat cover. These findings suggest that climate change may have serious implications for earthworm communities and for the functions they provide.

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.

Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

Abstract: Estimation of landslide susceptibility is still an ongoing requirement for land use management plans. Here, we proposed two novel intelligence hybrid models that rely on an adaptive neuro-fuzzy inference system (ANFIS) and two metaheuristic optimization algorithms, i.e., grey wolf optimizer (GWO) and biogeography-based optimization (BBO), for obtaining a reliable estimate of landslide susceptibility. Sixteen causative factors and 391 historical landslide events from a landslide-prone area of the State of Uttarakhand, northern India, were used to generate a geospatial database. The ANFIS model was employed to develop an initial landslide susceptibility model that was then optimized using the GWO and BBO algorithms. This resulted in two novel models, i.e., ANFIS-BBO and ANFIS-GWO, that benefited from an intelligent approach to automatically and properly adjust the best parameters of the base ANFIS model for the prediction of landslide susceptibilities. The robustness of the models was verified through a large number of runs using different splits of training and validation datasets. Although few differences observed between the predictive capability of the models (AUCANFIS-BBO = 0.95; RMSEANFIS-BBO = 0.316 vs. ACUANFIS-GWO = 0.94; RMSEANFIS-GWO = 0.322), the Wilcoxon signed-rank test indicated a significant difference between the model performances in both training and validation datasets. Overall, our proposed models demonstrated an improved prediction of landslides compared to those achieved in previous studies with other methods. Therefore, these novel models can be recommended for modeling landslide susceptibility, and the modelers can easily tailor their use based on their individual circumstances.

sPlot – A new tool for global vegetation analyses

Abstract: Aims :Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Biological, nutritional, and therapeutic significance of Moringa oleifera Lam

Abstract: The genus Moringa Adans. comprises 13 species, of which Moringa oleifera Lam. native to India and cultivated across the world owing to its drought and frost resistance habit is widely used in traditional phytomedicine and as rich source of essential nutrients. Wide spectrum of phytochemical ingredients among leaf, flower, fruit, seed, seed oil, bark, and root depend on cultivar, season, and locality. The scientific studies provide insights on the use of M. oleifera with different aqueous, hydroalcoholic, alcoholic, and other organic solvent preparations of different parts for therapeutic activities, that is, antibiocidal, antitumor, antioxidant, anti-inflammatory, cardio-protective, hepato-protective, neuro-protective, tissue-protective, and other biological activities with a high degree of safety. A wide variety of alkaloid and sterol, polyphenols and phenolic acids, fatty acids, flavanoids and flavanol glycosides, glucosinolate and isothiocyanate, terpene, anthocyanins etc. are believed to be responsible for the pragmatic effects. Seeds are used with a view of low-cost biosorbent and coagulant agent for the removal of metals and microbial contamination from waste water. Thus, the present review explores the use of M. oleifera across disciplines for its prominent bioactive ingredients, nutraceutical, therapeutic uses and deals with agricultural, veterinarian, biosorbent, coagulation, biodiesel, and other industrial properties of this "Miracle Tree."

Marginal Agricultural Land Low-Input Systems for Biomass Production

Abstract: This study deals with approaches for a social-ecological friendly European bioeconomy based on biomass from industrial crops cultivated on marginal agricultural land. The selected crops to be investigated are: Biomass sorghum, camelina, cardoon, castor, crambe, Ethiopian mustard, giant reed, hemp, lupin, miscanthus, pennycress, poplar, reed canary grass, safflower, Siberian elm, switchgrass, tall wheatgrass, wild sugarcane, and willow. The research question focused on the overall crop growth suitability under low-input management. The study assessed: (i) How the growth suitability of industrial crops can be defined under the given natural constraints of European marginal agricultural lands; and (ii) which agricultural practices are required for marginal agricultural land low-input systems (MALLIS). For the growth-suitability analysis, available thresholds and growth requirements of the selected industrial crops were defined. The marginal agricultural land was categorized according to the agro-ecological zone (AEZ) concept in combination with the marginality constraints, so-called ‘marginal agro-ecological zones’ (M-AEZ). It was found that both large marginal agricultural areas and numerous agricultural practices are available for industrial crop cultivation on European marginal agricultural lands. These results help to further describe the suitability of industrial crops for the development of social-ecologically friendly MALLIS in Europe.

Hybrid computational intelligence models for groundwater potential mapping

Abstract: Groundwater is the most important natural resource in many parts of the world that requires advanced new technologies for monitoring and control. This study presents a comparative analysis of three novel hybrid computational intelligence models that consist of a base Decision Stump classifier and three ensemble learning techniques, i.e., Rotation Forest, MultiBoost, and Bagging, for the groundwater potential mapping. Ten influencing factors (i.e., slope, aspect, plan curvature, topographic wetness index, rainfall, river density, lithology, land use, and soil) and 34 groundwater wells from the Vadodara district, Gujarat, India, were used to prepare a geospatial database. Using this database, three hybrid groundwater models, i.e., Rotation Forest based Decision Stump, MultiBoost based Decision Stump, and Bagging based Decision Stump, were developed. Based on a variety of performance metrics, it is revealed that the Rotation Forest based Decision Stump model had the best performance, followed by the MultiBoost based Decision Stump and Bagging based Decision Stump models. However, all the novel hybrid computational models presented here provided improved estimates of groundwater potential compared to those in previous studies and are sufficiently general to be used in many different landscapes around the world.

Important role of forest disturbances in the global biomass turnover and carbon sinks

Abstract: Forest disturbances that lead to the replacement of whole tree stands are a cornerstone of forest dynamics, with drivers that include fire, windthrow, biotic outbreaks and harvest. The frequency of disturbances may change over the next century with impacts on the age, composition and biomass of forests. However, the disturbance return time, that is, the mean interval between disturbance events, remains poorly characterized across the world’s forested biomes, which hinders the quantification of the role of disturbances in the global carbon cycle. Here we present the global distribution of stand-replacing disturbance return times inferred from satellite-based observations of forest loss. Prescribing this distribution within a vegetation model with a detailed representation of stand structure, we quantify the importance of stand-replacing disturbances for biomass carbon turnover globally over 2001–2014. The return time varied from less than 50 years in heavily managed temperate ecosystems to over 1,000 years in tropical evergreen forests. Stand-replacing disturbances accounted for 12.3% (95% confidence interval, 11.4–13.7%) of the annual biomass carbon turnover due to tree mortality globally, and in 44% of the forested area, biomass stocks are strongly sensitive to changes in the disturbance return time. Relatively small shifts in disturbance regimes in these areas would substantially influence the forest carbon sink that currently limits climate change by offsetting emissions. Forest stand-replacing disturbances significantly affect the biomass stocks in about a half of forested area globally, according to analyses of global forest loss from satellite data, together with a dynamic vegetation model.

Screening for Fusarium Antagonistic Bacteria From Contrasting Niches Designated the Endophyte Bacillus halotolerans as Plant Warden Against Fusarium.

Abstract: Date palm (Phoenix dactylifera L.) plantations in North Africa are nowadays threatened with the spread of the Bayoud disease caused by Fusarium oxysporum f. sp. albedinis, already responsible for destroying date production in other infected areas, mainly in Morocco. Biological control holds great promise for sustainable and environmental-friendly management of the disease. In this study, the additional benefits to agricultural ecosystems of using plant growth promoting rhizobacteria (PGPR) or endophytes are addressed. First, PGPR or endophytes can offer an interesting bio-fertilization, meaning that it can add another layer to the sustainability of the approach. Additionally, screening of contrasting niches can yield bacterial actors that could represent wardens against whole genera or groups of plant pathogenic agents thriving in semi-arid to arid ecosystems. Using this strategy, we recovered four bacterial isolates, designated BFOA1, BFOA2, BFOA3 and BFOA4, that proved very active against F. oxysporum f. sp. albedinis. BFOA1-BFOA4 proved also active against 16 Fusarium isolates belonging to four species: F. oxysporum (with strains phytopathogenic of Olea europaea and tomato), F. solani (with different strains attacking O. europaea and potato), F. acuminatum (pathogenic on O. europaea) and F. chlamydosporum (phytopathogenic of O. europaea). BFOA1-BFOA4 bacterial isolates exhibited strong activities against another four major phytopathogens: Botrytis cinerea, Alternaria alternata, Phytophthora infestans, and Rhizoctonia bataticola. Isolates BFOA1-BFOA4 had the ability to grow at temperatures up to 35°C, pH range of 5-10, and tolerate high concentrations of NaCl and up to 30% PEG. The isolates also showed relevant direct and indirect PGP features, including growth on nitrogen-free medium, phosphate solubilization and auxin biosynthesis, as well as resistance to metal and xenobiotic stress. Phylogenomic analysis of BFOA1-BFOA4 isolates indicated that they all belong to Bacillus halotolerans, which could therefore considered as a warden against Fusarium infection in plants. Comparative genomics allowed us to functionally describe the open pan genome of B. halotolerans and LC-HRMS and GCMS analyses, enabling the description of diverse secondary metabolites including pulegone, 2-undecanone, and germacrene D, with important antimicrobial and insecticidal properties. In conclusion, B. halotolerans could be used as an efficient bio-fertilizer and bio-control agent in semi-arid and arid ecosystems.

Assessing vulnerability of forest ecosystem in the Indian Western Himalayan region using trends of net primary productivity

Abstract: The Himalayan ecosystem is one of the sensitive and fragile ecosystems with rich biodiversity that provides major ecosystem services. The study was conducted to measure the extent of vulnerability across forested grids of Uttarakhand—one of the States of Indian Western Himalayan (IWH) region. The forests of the state are exposed to various anthropogenic and natural climatic pressures, thus making them vulnerable. In this paper, we demonstrate how to map vulnerability of forest ecosystem by analyzing variability and trends of net primary productivity (NPP). The vulnerability of the forest ecosystem was evaluated through trends of sensitivity and adaptability of NPP. The sensitivity of a system was considered as the response degree of the system to climatic variability whereas adaptability was considered as the ability to maintain, recover or improve its structure in the face of climatic stresses. In our study, NPP was considered as the receptor of shock and stresses of climatic variability and human disturbances. We discuss the method and results with reference to productivity changes under the influence of changing climate for the forested landscape of a mountainous region. The results have been summarized to rank vulnerability at the level of administrative boundary of governance, i.e. district. Average value of vulnerability for all NPP pixels of forests grids in a district was used to compute the vulnerability at district level. The study will help forest managers in decision making for efficiently allocating resources and to prioritize management options in the identified regions to improve productivity in coming times.

Forest carbon allocation modelling under climate change.

Abstract: Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

Discovery of Ganoderma lucidum triterpenoids as potential inhibitors against Dengue virus NS2B-NS3 protease.

Abstract: Dengue virus (DENV) infection causes serious health problems in humans for which no drug is currently available. Recently, DENV NS2B-NS3 protease has been proposed as a primary target for anti-dengue drug discovery due to its important role in new virus particle formation by conducting DENV polyprotein cleavage. Triterpenoids from the medicinal fungus Ganoderma lucidum have been suggested as pharmacologically bioactive compounds and tested as anti-viral agents against various viral pathogens including human immunodeficiency virus. However, no reports are available concerning the anti-viral activity of triterpenoids from Ganoderma lucidum against DENV. Therefore, we employed a virtual screening approach to predict the functional triterpenoids from Ganoderma lucidum as potential inhibitors of DENV NS2B-NS3 protease, followed by an in vitro assay. From in silico analysis of twenty-two triterpenoids of Ganoderma lucidum, four triterpenoids, viz. Ganodermanontriol (−6.291 kcal/mol), Lucidumol A (−5.993 kcal/mol), Ganoderic acid C2 (−5.948 kcal/mol) and Ganosporeric acid A (−5.983 kcal/mol) were predicted to be viral protease inhibitors by comparison to reference inhibitor 1,8-Dihydroxy-4,5-dinitroanthraquinone (−5.377 kcal/mol). These results were further studied for binding affinity and stability using the molecular mechanics/generalized Born surface area method and Molecular Dynamics simulations, respectively. Also, in vitro viral infection inhibition suggested that Ganodermanontriol is a potent bioactive triterpenoid.

Propagation from root cuttings for black locust (Robinia pseudoacacia L.) improvement in Hungary: a review.

Abstract: Black locust (Robinia pseudoacacia L.) is a valuable stand-forming tree species introduced to Europe approximately 400 years ago from North America. Today it is widely planted throughout the world, first of all for wood production. In Hungary, where black locust has great importance in the forest management, it is mainly propagated by seeds. But since the seed-raised plants present a great genetic variation, this type of propagation can not be used for Robinia’s improved cultivars. In the Hungarian black locust clonal forestry, propagation from root cuttings can be used for reproduction of superior individuals or cultivars in large quantities. However, this method demands more care than raising seedlings from seeds and can be applied with success in well-equipped nurseries.

Identifying the tree species compositions that maximize ecosystem functioning in European forests

Abstract: 1. Forest ecosystem functioning generally benefits from higher tree species richness, but variation within richness levels is typically large. This is mostly due to the contrasting performances of ...

Maintenance of long-term experiments for unique insights into forest growth dynamics and trends: review and perspectives

Abstract: In this review, the unique features and facts of long-term experiments are presented. Long-term experimental plots provide information of forest stand dynamics which cannot be derived from forest inventories or small temporary plots. Most comprise unthinned plots which represent the site specific maximum stand density as an unambiguous reference. By measuring the remaining as well as the removed stand, the survey of long-term experiments provides the total production at a given site, which is most relevant for examining the relationship between site conditions and stand productivity on the one hand and between stand density and productivity on the other. Thus, long-term experiments can reveal the site-specific effect of thinning and species mixing on stand structure, production and carbon sequestration. If they cover an entire rotation or even the previous and following generation on a given site, they reveal a species’ long-term behaviour and any growth trends caused by environmental changes. Second, we exploit the unique data of European long-term experiments, some of which have been surveyed since 1848. We show the long-term effect of different density regimes on stand dynamics and an essential trade-off between total stand volume production and mean tree size. Long-term experiments reveal that tree species mixing can significantly increase stand density and productivity compared with monospecific stands. Thanks to surveys spanning decades or even a century, we can show the changing long-term-performance of different provenances and acceleration of stand production caused by environmental change, as well as better understand the growth dynamics of natural forests. Without long-term experiments forest science and practice would be not in a position to obtain such findings which are of the utmost relevance for science and practice. Third, we draw conclusions and show perspectives regarding the maintenance and further development of long-term experiments. It would require another 150 years to build up a comparable wealth of scientific information, practical knowledge, and teaching and training model examples. Although tempting, long-term experiments should not be sacrificed for cost-cutting measures. Given the global environmental change and the resulting challenges for sustainable management, the network of long-term experiments should rather be extended regarding experimental factors, recorded variables and inter- and transdisciplinary use for science and practice.

Right on track? Performance of satellite telemetry in terrestrial wildlife research

Abstract: Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Abstract: Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

A nexus approach for the MENA region-from concept to knowledge to action

Abstract: There is wide agreement that a nexus or integrated approach to managing and governing natural resources such as land, water, and energy can improve environmental, climate, human, and political security. However, few if any countries in the MENA region have made progress in implementing such an approach. There appear to be several constraints inhibiting the development and adoption of nexus approaches. These constraints include strong sectoral silos, insufficient incentives for integrated planning and policy making at all levels, and limited vision, knowledge, and practical experience to guide successful implementation. In turn, the limited implementation and hence lack of empirical evidence of a nexus approach, which could demonstrate its benefits, does little to strengthen political will for the development of adequate incentives, structures, and procedures. Against this backdrop, this paper presents five case studies which take an integrated approach, in three MENA countries, namely Jordan, Lebanon, and Morocco. Based on an analytical framework developed here, the paper analyses and compares the success factors for nexus implementation, and also for transfer and upscaling. The analysis emphasizes the need for appropriate framework conditions, targeted investments and pioneering actors, to make integrated approaches across sectors and levels work. With the evidence presented, the paper aims to set in motion a positive or virtuous cycle of generating more nexus evidence, improved framework conditions, further nexus implementation on the ground, and from that even more nexus evidence. Finally, the paper contributes to overcoming the repeated requests for better definition and conceptualization of the nexus, which often has slowed down adoption of the concept.