Search results for: forest garden

Authors: María Graciela Aguayo, Laura Reyes, Claudia Oviedo, José Navarrete, Liset Gómez, Hugo Torres

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Most wood species used in construction deteriorate when exposed to environmental conditions that favor wood-degrading organisms’ growth. Therefore, chemical protection by impregnation allows more efficient use of forest resources extending the wood useful life. A wood protection treatment which has attracted considerable interest in the scientific community during the last decade is wood impregnation with nano compounds. Radiata pine is the main wood species used in the Chilean construction industry, with total availability of 8 million m³ sawn timber. According to the requirements of the American Wood Protection Association (AWPA) and the Chilean Standards (NCh) radiata pine timber used in construction must be protected due to its low natural durability. In this work, the impregnation with copper nanoparticles (CuNP) was studied in terms of penetration and its protective effect against wood rot fungi. Two concentrations: 1 and 3 g/L of NPCu were applied by impregnation on radiata pine sapwood. Test penetration under AWPA A3-91 standard was carried out, and wood decay tests were performed according to EN 113, with slight modifications. The results of penetration for 1 g/L CuNP showed an irregular total penetration, and the samples impregnated with 3 g/L showed a total penetration with uniform concentration (blue color in all cross sections). The impregnation wood mass losses due to fungal exposure were significantly reduced, regardless of the concentration of the solution or the fungus. In impregnated wood samples, exposure to G. trabeum resulted ML values of 2.70% and 1.19% for 1 g/L and 3 g/L CuNP, respectively, and exposure to P. placenta resulted in 4.02% and 0.70%-ML values for 1 g/L and 3 g/L CuNP, respectively. In this study, the penetration analysis confirmed a uniform distribution inside the wood, and both concentrations were effective against the tested fungi, giving mass loss values lower than 5%. Therefore, future research in wood preservatives should focus on new nanomaterials that are more efficient and environmentally friendly. Acknowledgments: CONICYT FONDEF IDeA I+D 2019, grant number ID19I10122.

Keywords: copper nanoparticles, fungal degradation, radiata pine wood, wood preservation

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: A. Berraf-Tebbal, Z. Bouznad, , A.J.L. Phillips

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Phaeomoniella is a fungus genus in the mitosporic ascomycota which includes Phaeomoniella chlamydospora specie associated with two declining diseases on grapevine (Vitis vinifera) namely Petri disease and esca. Recent studies have shown that several Phaeomoniella species also cause disease on many other woody crops, such as forest trees and woody ornamentals. Two new species, Phaeomoniella zymoides and Phaeomoniella pinifoliorum H.B. Lee, J.Y. Park, R.C. Summerbell et H.S. Jung, were isolated from the needle surface of Pinus densiflora Sieb. et Zucc. in Korea. The identification of species in Phaeomoniella genus can be a difficult task if based solely on morphological and cultural characters. In this respect, the application of molecular methods, particularly PCR-based techniques, may provide an important contribution. MSP-PCR (microsatellite primed-PCR) fingerprinting has proven useful in the molecular typing of fungal strains. The high discriminatory potential of this method is particularly useful when dealing with closely related or cryptic species. In the present study, the application of PCR fingerprinting was performed using the micro satellite primer M13 for the purpose of species identification and strain typing of 84 Phaeomoniella -like isolates collected from grapevines with typical symptoms of dieback. The bands produced by MSP-PCR profiles divided the strains into 3 clusters and 5 singletons with a reproducibility level of 80%. Representative isolates from each group and, when possible, isolates from Eutypa dieback and esca symptoms were selected for sequencing of the ITS region. The ITS sequences for the 16 isolates selected from the MSP-PCR profiles were combined and aligned with sequences of 18 isolates retrieved from GenBank, representing a selection of all known Phaeomoniella species. DNA sequences were compared with those available in GenBank using Neighbor-joining (NJ) and Maximum-parsimony (MP) analyses. The phylogenetic trees of the ITS region revealed that the Phaeomoniella isolates clustered with Phaeomoniella chlamydospora reference sequences with a bootstrap support of 100 %. The complexity of the pathosystems vine-trunk diseases shows clearly the need to identify unambiguously the fungal component in order to allow a better understanding of the etiology of these diseases and justify the establishment of control strategies against these fungal agents.

Keywords: Genotyping, MSP-PCR, ITS, phylogeny, trunk diseases

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Authors: Erika Csanyi, Gyula Sandor

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In the course of the examination, we sought to answer the question of how and to what extent the home range and daily activity of a deer stag relocated from its habitual surroundings changes. We conducted the examination in two hunting areas in Hungary, about 50 km from one another. The control area was in the north of Somogy County, while the sample area was an area of similar features in terms of forest cover, tree stock, agricultural structure, altitude above sea level, climate, etc. in the south of Somogy County. Three middle-aged red deer stags were captured with rocket nets, immobilized and marked with GPS-Plus Collars manufactured by Vectronic Aerospace Gesellschaft mit beschränkter Haftung. One captured species was relocated. We monitored deer movements over 24-hour periods at 3 months. In the course of the examination, we analysed the behaviour of the relocated species and those that remained in their original habitat, as well as the temporal evolution of their behaviour. We examined the characteristics of the marked species’ daily activities and the hourly distance they covered. We intended to find out the difference between the behaviour of the species remaining in their original habitat and of those relocated to a more distant, but similar habitat. In summary, based on our findings, it can be established that such enforced relocations to a different habitat (e.g., game relocation) significantly increases the home range of the species in the months following relocation. Home ranges were calculated using the full data set and the minimum convex polygon (MCP) method. Relocation did not increase the nocturnal and diurnal movement activity of the animal in question. Our research found that the home range of the relocated species proved to be significantly higher than that of those species that were not relocated. The results have been presented in tabular form and have also been displayed on a map. Based on the results, it can be established that relocation inherently includes the risk of falling victim to poaching, vehicle collision. It was only in the third month following relocation that the home range of the relocated species subsided to the level of those species that were not relocated. It is advisable to take these observations into consideration in relocating red deer for nature conservation or game management purposes.

Keywords: Cervus elaphus, home range, relocation, red deer stag

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Authors: Pratima Poudel, Austin Himes, Heidi Renninger, Eric McConnel

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Populus spp. (poplar) are the fastest-growing trees in North America, making them ideal for a range of applications as they can achieve high yields on short rotations and regenerate by coppice. Furthermore, poplar undergoes biochemical conversion to fuels without complexity, making it one of the most promising, purpose-grown, woody perennial energy sources. Employing wood-based biomass for bioenergy offers numerous benefits, including reducing greenhouse gas (GHG) emissions compared to non-renewable traditional fuels, the preservation of robust forest ecosystems, and creating economic prospects for rural communities.In order to gain a better understanding of the potential use of poplar as a biomass feedstock for biofuel in the southeastern US, the conducted a techno-economic assessment (TEA). This assessment is an analytical approach that integrates technical and economic factors of a production system to evaluate its economic viability. the TEA specifically focused on a short rotation coppice system employing a single-pass cut-and-chip harvesting method for poplar. It encompassed all the costs associated with establishing dedicated poplar plantations, including land rent, site preparation, planting, fertilizers, and herbicides. Additionally, we performed a sensitivity analysis to evaluate how different costs can affect the economic performance of the poplar cropping system. This analysis aimed to determine the minimum average delivered selling price for one metric ton of biomass necessary to achieve a desired rate of return over the cropping period. To inform the TEA, data on the establishment, crop care activities, and crop yields were derived from a field study conducted at the Mississippi Agricultural and Forestry Experiment Station's Bearden Dairy Research Center in Oktibbeha County and Pontotoc Ridge-Flatwood Branch Experiment Station in Pontotoc County.

Keywords: biomass, populus species, sensitivity analysis, technoeconomic analysis

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Authors: Gadisa Demie, Mesele Negash, Zerihun Asrat, Lojka Bohdan

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Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) is a suitable land-use option for tackling such declines in ecosystem services, including climate change mitigation. However, it is unclear how biomass models, AF practices, and socio-ecological factors determine these roles, which hinders the implementation of climate change mitigation initiatives. This study aimed to estimate the ecosystem C stocks of the studied AF practices in relation to socio-ecological variables in central Ethiopia. Out of 243 AF farms inventoried, 108 were chosen at random from three AF practices to estimate their biomass and soil organic carbon. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths; 216 samples were taken for each soil organic carbon fraction (%C) and bulk density computation. The study found that the currently developed allometric equations were the most accurate to estimate biomass C for trees growing in the landscape when compared to previous models. The study found higher overall biomass C in woodlots (165.62 Mg ha-¹) than in homegardens (134.07 Mg ha-¹) and parklands (19.98 Mg ha-¹). Conversely, overall, SOC was higher for homegardens (143.88 Mg ha-¹), but lower for parklands (53.42 Mg ha-¹). The ecosystem C stock was comparable between homegardens (277.95 Mg ha-¹) and woodlots (275.44 Mg ha-¹). The study found that elevation, wealthy levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass and ecosystem C stocks but non-significant with slope (P > 0.05). Similarly, SOC increased with increasing elevation, AF farm age, and wealthy status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P <0.05) effect on overall biomass C stocks in homegardens. The overall study highlights that AF practices have a great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers.

Keywords: agricultural landscape, biomass, climate change, soil organic carbon

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Authors: Samhita Mummadi, Sree Divya Nagalli, Harshini Vemuri, Saketh Charan Nakka, Sumesh K. J.

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One of the most significant challenges faced by people in today’s digital era is an alarming increase in fraudulent activities on online platforms. The fascination with online shopping to avoid long queues in shopping malls, the availability of a variety of products, and home delivery of goods have paved the way for a rapid increase in vast online shopping platforms. This has had a major impact on increasing fraudulent activities as well. This loop of online shopping and transactions has paved the way for fraudulent users to commit fraud. For instance, consider a store that orders thousands of products all at once, but what’s fishy about this is the massive number of items purchased and their transactions turning out to be fraud, leading to a huge loss for the seller. Considering scenarios like these underscores the urgent need to introduce machine learning approaches to combat fraud in online shopping. By leveraging robust algorithms, namely KNN, Decision Trees, and Random Forest, which are highly effective in generating accurate results, this research endeavors to discern patterns indicative of fraudulent behavior within transactional data. Introducing a comprehensive solution to this problem in order to empower e-commerce administrators in timely fraud detection and prevention is the primary motive and the main focus. In addition to that, sentiment analysis is harnessed in the model so that the e-commerce admin can tailor to the customer’s and consumer’s concerns, feedback, and comments, allowing the admin to improve the user’s experience. The ultimate objective of this study is to ramp up online shopping platforms against fraud and ensure a safer shopping experience. This paper underscores a model accuracy of 84%. All the findings and observations that were noted during our work lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as technologies continue to evolve.

Keywords: behavior analysis, feature selection, Fraudulent pattern recognition, imbalanced classification, transactional anomalies

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Authors: Rahmi Kafadar, Levent Genc

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In present study, it was aimed to determine potential agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale province, Turkey. Seven-band Landsat 8 OLI images acquired on July 12 and August 13, 2013, and their 14-band combination image were used to identify current Land Use Land Cover (LULC) status. Principal Component Analysis (PCA) was applied to three Landsat datasets in order to reduce the correlation between the bands. A total of six Original and PCA images were classified using supervised classification method to obtain the LULC maps including 6 main classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area-Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was performed by checking the accuracy of 120 randomized points for each LULC maps. The best overall accuracy and Kappa statistic values (90.83%, 0.8791% respectively) were found for PCA images which were generated from 14-bands combined images called 3-B/JA. Digital Elevation Model (DEM) with 15 m spatial resolution (ASTER) was used to consider topographical characteristics. Soil properties were obtained by digitizing 1:25000 scaled soil maps of rural services directorate general. Potential Agricultural Lands (PALs) were determined using Geographic information Systems (GIS). Procedure was applied considering that “Other” class of LULC map may be used for agricultural purposes in the future properties. Overlaying analysis was conducted using Slope (S), Land Use Capability Class (LUCC), Other Soil Properties (OSP) and Land Use Capability Sub-Class (SUBC) properties. A total of 901.62 ha areas within “Other” class (15798.2 ha) of LULC map were determined as PALs. These lands were ranked as “Very Suitable”, “Suitable”, “Moderate Suitable” and “Low Suitable”. It was determined that the 8.03 ha were classified as “Very Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate Suitable” for PALs. In addition, 756.56 ha were found to be “Low Suitable”. The results obtained from this preliminary study can serve as basis for further studies.

Keywords: digital elevation model (DEM), geographic information systems (GIS), gokceada (Imroz), lANDSAT 8 OLI-TIRS, land use land cover (LULC)

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

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Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Mohamed Thani Ibouroi, Ali Cheha, Claudine Montgelard, Veronique Arnal, Dawiyat Massoudi, Guillelme Astruc, Said Ali Ousseni Dhurham, Aurelien Besnard

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The Livingstone's flying fox (Pteropus livingstonii) and the Comorian fruit bat (P.seychellensis comorensis) are two endemic fruit bat species among the mostly threatened animals of the Comoros archipelagos. Despite their role as important ecosystem service providers like all flying fox species as pollinators and seed dispersers, little is known about their ecologies, population genetics and structures making difficult the development of evidence-based conservation strategies. In this study, we assess spatial distribution and ecological niche of both species using Species Distribution Modeling (SDM) based on the recent Ensemble of Small Models (ESMs) approach using presence-only data. Population structure and genetic diversity of the two species were assessed using both mitochondrial and microsatellite markers based on non-invasive genetic samples. Our ESMs highlight a clear niche partitioning of the two sympatric species. Livingstone’s flying fox has a very limited distribution, restricted on steep slope of natural forests at high elevation. On the contrary, the Comorian fruit bat has a relatively large geographic range spread over low elevations in farmlands and villages. Our genetic analysis shows a low genetic diversity for both fruit bats species. They also show that the Livingstone’s flying fox population of the two islands were genetically isolated while no evidence of genetic differentiation was detected for the Comorian fruit bats between islands. Our results support the idea that natural habitat loss, especially the natural forest loss and fragmentation are the important factors impacting the distribution of the Livingstone’s flying fox by limiting its foraging area and reducing its potential roosting sites. On the contrary, the Comorian fruit bats seem to be favored by human activities probably because its diets are less specialized. By this study, we concluded that the Livingstone’s flying fox species and its habitat are of high priority in term of conservation at the Comoros archipelagos scale.

Keywords: Comoros islands, ecological niche, habitat loss, population genetics, fruit bats, conservation biology

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Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

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Authors: Emiru Birhane, Tesfay Gidey, Haftu Abrha, Abrha Brhan, Amanuel Zenebe, Girmay Gebresamuel, Florent Noulèkoun

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Dracaena ombet and Dobera glabra are two of the most rare and endangered tree species in dryland areas. Unfortunately, their sustainability is being compromised by different anthropogenic and natural factors. However, the impacts of ongoing land use and climate change on the population structure and distribution of the species are less explored. This study was carried out in the grazing lands and hillside areas of the Desa'a dry Afromontane forest, northern Ethiopia, to characterize the population structure of the species and predict the impact of climate change on their potential distributions. In each land-use type, abundance, diameter at breast height, and height of the trees were collected using 70 sampling plots distributed over seven transects spaced one km apart. The geographic coordinates of each individual tree were also recorded. The results showed that the species populations were characterized by low abundance and unstable population structure. The latter was evinced by a lack of seedlings and mature trees. The study also revealed that the total abundance and dendrometric traits of the trees were significantly different between the two land uses. The hillside areas had a denser abundance of bigger and taller trees than the grazing lands. Climate change predictions using the MaxEnt model highlighted that future temperature increases coupled with reduced precipitation would lead to significant reductions in the suitable habitats of the species in northern Ethiopia. The species' suitable habitats were predicted to decline by 48–83% for D. ombet and 35–87% for D. glabra. Hence, to sustain the species populations, different strategies should be adopted, namely the introduction of alternative livelihoods (e.g., gathering NTFP) to reduce the overexploitation of the species for subsistence income and the protection of the current habitats that will remain suitable in the future using community-based exclosures. Additionally, the preservation of the species' seeds in gene banks is crucial to ensure their long-term conservation.

Keywords: grazing lands, hillside areas, land-use change, MaxEnt, range limitation, rare and endangered tree species

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Authors: Luciana Salomon

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The Andes hold one of the highest plant species diversity in the world. How such diversity originated is one of the most intriguing questions in studies addressing the pattern of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as major triggers of this spectacular diversity. The Andes are one of the most species-rich area for the largest genus from the Asteraceae family, Senecio. There, the genus presents an incredible variation in growth form and ecological niche space. If this diversity of Andean Senecio can be explained by a monophyletic origin and subsequent radiation has not been tested up to now. Previous studies trying to disentangle the evolutionary history of some Andean Senecio struggled with the relatively low resolution and support of the phylogenies, which is indicative of recently radiated groups. Using Hyb-Seq, a powerful approach is available to address phylogenetic questions in groups whose evolutionary histories are recent and rapid. This approach was used for Senecio to build a phylogenetic backbone on which to study the mechanisms shaping its hyper-diversity in the Andes, focusing on Senecio ser. Culcitium, an exclusively Andean and well circumscribed group presenting large morphological variation and which is widely distributed across the Andes. Hyb-Seq data for about 130 accessions of Seneciowas generated. Using standard data analysis work flows and a newly developed tool to utilize paralogs for phylogenetic reconstruction, robustness of the species treewas investigated. Fully resolved and moderately supported species trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within this group, some species formed well-supported clades congruent with morphology, while some species would not have exclusive ancestry, in concordance with previous studies showing a geographic differentiation. Additionally, paralogs were detected for a high number of loci, indicating duplication events and hybridization, known to be common in Senecio ser. Culcitium might have lead to hybrid speciation. The rapid diversification of the group seems to have followed a south-north distribution throughout the Andes, having accelerated in the conquest of new habitats more recently available: i.e., Montane forest, Paramo, and Superparamo.

Keywords: evolutionary radiations, andes, paralogy, hybridization, senecio

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Authors: Julius Niba Fon, Jean Hude E. Moudingo

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Mangrove ecosystems in Cameroon are valuable both in services and functions as they play host to carbon sinks, fishery breeding grounds and natural coastal barriers against storms. In addition to the globally important biodiversity that they contain, they also contribute to local livelihoods. Despite these appraisals, a reduction of about 30 % over a 25 years period due to anthropogenic and natural actions has been recorded. The key drivers influencing mangrove change include population growth, climate change, economic and political trends and upstream habitat use. Reversing the trend of mangrove loss and growing vulnerability of coastal peoples requires a real commitment by the government to develop and implement robust level policies. It has been observed in Cameroon that special ecosystems like mangroves are insufficiently addressed by forestry and/or environment programs. Given these facts, the Food Agriculture Organization (FAO) in partnership with the Government of Cameroon and other development actors have put in place the project for sustainable community-based management and conservation of mangrove ecosystems in Cameroon. The aim is to address two issues notably the present weak institutional and legal framework for mangrove management, and the unrestricted and unsustainable harvesting of mangrove resources. Civil society organizations like the Cameroon Wildlife Conservation Society, Cameroon Ecology and Organization for the Environment and Development have been working to reduce the deforestation and degradation trend of Cameroon mangroves and also bringing the mangrove agenda to the fore in national and international arenas. Following a desktop approach, we found out that in situ and ex situ initiatives on mangrove management and conservation exist on propagation of improved fish smoke ovens to reduce fuel wood consumption, mangrove forest regeneration, shrimps farming and mangrove protected areas management. The evidence generated from the field experiences are inputs for processes of improving the legal and institutional framework for mangrove management in Cameroon, such as the elaboration of norms for mangroves management engaged by the government.

Keywords: mangrove ecosystem, legal and institutional framework, climate change, civil society organizations

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Authors: Abdelrahman Elsehsah

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Land Use and Land Cover (LULC) dynamics in Riyadh over a decade were comprehensively analyzed using the Google Earth Engine (GEE) platform. By harnessing the Landsat 8 Image collection and night-time light image collection from May to August for the years 2013 and 2023, we were able to generate insightful datasets capturing the changing landscape of the region. Our approach involved a Random Forest (RF) classification model that consistently displayed commendable precision scores above 92% for both years. A notable discovery from the study was the pronounced urban expansion, particularly around Riyadh city. Within a mere ten-year span, urbanization surged noticeably, affecting the broader ecological environment of the region. Interestingly, the northeastern part of Riyadh emerged as a focal point of this growth, signaling rapid urban growth of urban sprawl and development. A comparison between the two years indicates a 21.51% increase in built-up areas, revealing the transformative pace of urban sprawl. Contrastingly, vegetation cover patterns presented a more nuanced picture. While our initial hypothesis predicted a decline in vegetation, the actual findings depicted both vegetation reduction in certain pockets and new growth in others, resulting in an overall 25.89% increase. This intricate pattern might be attributed to shifting agricultural practices, afforestation efforts, or even satellite image timings not aligning with seasonal vegetation growth. The bare soil, predominant in the desert landscape of Riyadh, saw a marginal reduction of 0.37% over the decade, challenging our initial expectations. Urban and agricultural advancements in Saudi Arabia appear to have slightly reduced the expanse of barren terrains. This study, underpinned by a rigorous methodological framework, reveals the multifaceted land cover changes in Riyadh in response to urban development and environmental factors. The precise, data-driven insights provided by our analysis serve as invaluable tools for understanding urban growth trajectories, guiding urban planning, policy formulation, and sustainable development endeavors in the region.

Keywords: remote sensing, KSA, ArcGIS, spatio-temporal

Procedia PDF Downloads 39

Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Pinus taeda, commonly known as loblolly pine, is a crucial timber species native to the southeastern USA. An emerging problem has been encountered for the past few years, which is better to be known as loblolly pine needle defoliation (LPND), which is threatening the ecological health of southeastern forests and economic vitality of the region’s timber industry. Currently, more than 1000 hectares of loblolly plantations in Alabama are affected with similar symptoms and have created concern among southeast landowners and forest managers. However, it is still uncertain whether LPND results from one or the combination of several fungal pathogens. Therefore, the objectives of the study were to identify and characterize the fungi associated with LPND in the southeastern USA and document the damage being done to loblolly pine as a result of repeated defoliation. Identification of fungi was confirmed using classical morphological methods (microscopic examination of the infected needles), conventional and species-specific priming (SSPP) PCR, and ITS sequencing. To date, 17 species of fungi, either cultured from pine needles or formed fruiting bodies on pine needles, were identified based on morphology and genetic sequence data. Among them, brown-spot pathogen Lecanostica acicola has been frequently recovered from pine needles in both spring and summer. Moreover, Ophistomatoid fungi such as Leptographium procerum, L. terebrantis are associated with pine decline have also been recovered from root samples of the infected stands. Trees have been increasingly and repeatedly chlorotic and defoliated from 2019 to 2020. Based on morphological observations and molecular data, emerging loblolly pine needle defoliation is due in larger part to the brown-spot pathogen L. acoicola followed by pine decline pathogens L. procerum and L. terebrantis. Root pathogens were suspected to emerge later, and their cumulative effects contribute to the widespread mortality of the trees. It is more likely that longer wet spring and warmer temperatures are favorable to disease development and may be important in the disease ecology of LPND. Therefore, the outbreak of the disease is assumed to be expanded over a large geographical area in a changing climatic condition.

Keywords: brown-spot fungi, emerging disease, defoliation, loblolly pine

Procedia PDF Downloads 139

Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

Procedia PDF Downloads 70

Authors: Janice Haworth, Karamoko Camara, Marie-Therèse Dramou, Kokoly Haba, Daniel Léno, Augustin Mara, Adama Noël Oulari, Silafa Tolno, Noël Zoumanigui

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The traditional rhythms of the West African country of Guinea have played a centuries-long role in defining the different people groups that make up the country. Throughout their history, before and since colonization by the French, the different ethnicities have used their traditional music as a distinct part of their historical identities. That is starting to change. Guinea is an impoverished nation created in the early twentieth-century with little regard for the history and cultures of the people who were included. The traditional rhythms of the different people groups and their heritages have remained. Fifteen individual traditional Guinean rhythms were chosen to represent popular rhythms from the four geographical regions of Guinea. Each rhythm was traced back to its native village and video recorded on-site by as many different local performing groups as could be located. The cyclical patterns rhythms were transcribed via a circular, spatial design and then copied into a box notation system where sounds happening at the same time could be studied. These rhythms were analyzed for their consistency-over-performance in a Fundamental Rhythm Pattern analysis so rhythms could be compared for how they are changing through different performances. The analysis showed that the traditional rhythm performances of the Middle and Forest Guinea regions were the most cohesive and showed the least evidence of change between performances. The role of music in each of these regions is both limited and focused. The Coastal and High Guinea regions have much in common historically through their ethnic history and modern-day trade connections, but the rhythm performances seem to be less consistent and demonstrate more changes in how they are performed today. In each of these regions the role and usage of music is much freer and wide-spread. In spite of advances being made as a country, different ethnic groups still frequently only respond and participate (dance and sing) to the music of their native ethnicity. There is some evidence that this self-imposed musical barrier is beginning to change and evolve, partially through the development of better roads, more access to electricity and technology, the nation-wide Ebola health crisis, and a growing self-identification as a unified nation.

Keywords: cultural identity, Guinea, traditional rhythms, west Africa

Procedia PDF Downloads 394

Authors: Yahoel Van Essen, Gordon Ho, Brett Russell, Hans-Georg Worms, Xiao Lin Long, Edward David Cooper, Avner Bachar

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Weeds reduce farm and forest productivity, invade crops, smother pastures and some can harm livestock. Farmers need to spend a significant amount of money to control weeds by means of biological, chemical, cultural, and physical methods. To solve the global agricultural labor shortage and remove poisonous chemicals, a fully autonomous, eco-friendly, and sustainable weeding technology is developed. This takes the form of a weeding robot, ‘Roboweeder’. Roboweeder includes a four-wheel-drive self-driving vehicle, a 4-DOF robotic arm which is mounted on top of the vehicle, an electromagnetic wave generator (magnetron) which is mounted on the “wrist” of the robotic arm, 48V battery packs, and a control/communication system. Cameras are mounted on the front and two sides of the vehicle. Using image processing and recognition, distinguish types of weeds are detected before being eliminated. The electromagnetic wave technology is applied to heat the individual weeds and clusters dielectrically causing them to wilt and die. The 4-DOF robotic arm was modeled mathematically based on its structure/mechanics, each joint’s load, brushless DC motor and worm gear’ characteristics, forward kinematics, and inverse kinematics. The Proportional-Integral-Differential control algorithm is used to control the robotic arm’s motion to ensure the waveguide aperture pointing to the detected weeds. GPS and machine vision are used to traverse the farm and avoid obstacles without the need of supervision. A Roboweeder prototype has been built. Multiple test trials show that Roboweeder is able to detect, point, and kill the pre-defined weeds successfully although further improvements are needed, such as reducing the “weeds killing” time and developing a new waveguide with a smaller waveguide aperture to avoid killing crops surrounded. This technology changes the tedious, time consuming and expensive weeding processes, and allows farmers to grow more, go organic, and eliminate operational headaches. A patent of this technology is pending.

Keywords: autonomous navigation, machine vision, precision heating, sustainable and eco-friendly

Procedia PDF Downloads 256

Authors: Sutida Maneeanakekul, Dusit Wechakit, Somsak Piriyayota

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Coastal erosion is a major problem in Thailand, in both the Gulf of Thailand and the Andaman Sea coasts. According to the Department of Marine and Coastal Resources, land erosion occurred along the 200 km coastline with an average rate of 5 meters/year. Coastal erosion affects public and government properties, as well as the socio-economy of the country, including emigration in coastal communities, loss of habitats, and decline in fishery production. To combat the problem of coastal erosion, projects utilizing bamboo sticks for coastal defense against erosion were carried out in 5 areas beginning in November, 2010, including: Pak Klong Munharn- Samut Songkhram Province; Ban Khun Samutmaneerat, Pak Klong Pramong and Chao Matchu Shrine-Samut Sakhon Province,and Pak Klong Hongthong – Chachoengsao Province by Marine and Coastal Resources Department. In 2012, an evaluation of the effectiveness of solving the problem of coastal erosion by using bamboo stick was carried out, with a focus on three aspects. Firstly, the change in physical and biological features after using the bamboo stick technique was assessed. Secondly, participation of people in the community in the way of managing the problem of coastal erosion were these aspects evaluated as part of the study. The last aspect that was evaluated is the satisfaction of the community toward this technique. The results of evaluation showed that the amounts of sediment have dramatically changed behind the bamboo sticks lines. The increase of sediment was found to be about 23.50-56.20 centimeters (during 2012-2013). In terms of biological aspect, there has been an increase in mangrove forest areas, especially at Bang Ya Prak, Samut Sakhon Province. Average tree density was found to be about 4,167 trees per square meter. Additionally, an increase in production of fisheries was observed. Presently, the change in the evaluated physical features tends to increase in every aspect, including the satisfaction of people in community toward the process of solving the erosion problem. People in the community are involved in the preparatory, operation, monitoring and evaluation process to resolve the problem in the medium levels.

Keywords: bamboo sticks, coastal erosion, rehabilitate, Thailand sustainable development approach

Procedia PDF Downloads 251

Authors: Anu Chandran, Reena Esther Rani

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Background of the Study: Dotted with multiple Unique Destination Prepositions (UDPs), Tamil Nadu is an established tourism brand as regards leisure, MICE, culture, and ecological flavors. Albeit, the enchanting destination possesses distinctive attributes and resources yet to be tapped for better competitive advantage. Being a destination that allures an incredible variety of migratory birds, Tamil Nadu is deemed to be an ornithologist’s paradise. This study primarily explores the prospects of developing Kaliveli, recognized as a bird sanctuary in the Tindivanam forest division of the Villupuram district in the State. Kaliveli is an ideal nesting site for migratory birds and is currently apt for a prospective analysis of regenerative tourism. Objectives of the study: This research lays an accent on avian tourism as part and parcel of sustainable tourism ventures. The impacts of projects like the Ornithological Conservation Centre on tourists have been gauged in the present paper. It maps the futuristic proactive propositions linked to regenerative tourism on the site. How far technological innovations can do a world of good in Kaliveli through Artificial Intelligence, Smart Tourism, and similar latest coinages to entice real eco-tourists, have been conceptualized. The experiential dimensions of resource stewardship as regards facilitating tourists’ relish the offerings in a sustainable manner is at the crux of this work. Methodology: Modeled as a case study, this work tries to deliberate on the impact of existing projects attributed to avian fauna in Kalveli. Conducted in the qualitative research design mode, the case study method was adopted for the processing and presentation of study results drawn by applying thematic content analysis based on the data collected from the field. Result and discussion: One of the key findings relates to the kind of nature trails that can be a regenerative dynamic for eco-friendly tourism in Kaliveli. Field visits have been conducted to assess the niche tourism aspects which could be incorporated with the regenerative tourism model to be framed as part of the study.

Keywords: regenerative tourism, Kaliveli bird sanctuary, sustainable development, resource Stewardship, Ornithology, Avian Fauna

Procedia PDF Downloads 81

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 43

Authors: Juan Facetti, Rocky McBride, Karina Loup

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The Chaco Region of Paraguay is a key biodiverse area for the conservation of jaguars (Panthera onca), the largest feline of the Americas. It comprises five eco-regions, which holds important but decreasing populations of this species. The last decades, the expansion of soybean over the Atlantic Forest, forced the translocation of cattle-ranches towards the Chaco. Few studies of Jaguar's population densities in the American hemisphere were done until now. In the region, the specie is listed as vulnerable or threatened and more information is needed to implement any conservation policy. Among the factors that threaten the populations are land-use change, habitat fragmentation, prey depletion and illegal hunting. Two largest eco-regions were studied: the Wet Chaco and the Dry Chaco. From 2002 more than 20 jaguars were captured and fitted with GPS-collar. Data collected from 11 GPS-collars were processed, transformed numerically and finally converted into maps for analyzing. 8.092 locations were determined for four adult females (AF) and one adult male (AM) in the Wet Chaco, and one AF, one juvenile male (JM) and four AM in the Dry Chaco, during 1,867 days. GIS and kernel methodology were used to calculate daily distance of movement, home range-HR (95% isopleth), and core area (considered as 50% isopleth). In the Wet Chaco HR were 56 Km2 and 238 km2 for females and males respectively; while in the Dry Chaco HR were 685 Km2 and 844.5 km2 for females and males respectively, and 172 Km2 for a juvenile. Core areas of individual activity for each jaguar, were on average 11.5 Km2 and 33.55 km2 for AF and AM respectively in the Wet Chaco, while in the Dry Chaco were larger: 115 km2 for five AM and 225 Km2 for an AF and 32.4 Km2 for a JM. In both ecoregions, only one relevant overlap of HR of adults was reported. During the reproduction season, the HR (95% K) of one AM overlapped 49.83% with that of one AF. At the Wet Chaco, the maximum daily distance moved by an AF was 14.5 Km and 11.6 Km for the AM, while the Maximum Mean Daily Moved (MMDM) distance was 5.6 km for an AF and 3.1 km for an AM. At the Dry Chaco, the maximum daily distance for an AF was 61.7Km., 50.9Km for the AM and 6.6 Km for the JM, while the MMDM distance was 13.2 km for an AM and 8.4 km for an AF. This study confirmed that, as the invasion to jaguar habitat increased, it resulted in fragmented landscapes that influence spacing patterns of jaguars. Males used largest HR that of the smaller females and males covers largest distances that of the females. There appeared to be important spatial segregation between not only females but also males. It is likely that the larger areas used by males are partly caused by the sexual dimorphism in body size that entails differences in prey requirements. These could explain the larger distances travelled daily by males.

Keywords: Chaco ecoregions, Jaguar, home range, Panthera onca, Paraguay

Procedia PDF Downloads 302

Authors: Zeynep Pirselimoglu Batman, Elvan Ender Altay, Murat Zencirkiran

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Water and water resources are characteristic areas with their special ecosystems Their natural, cultural and economic value and recreation opportunities are high. Recreational activities differ according to the natural, cultural, socio-economic resource values of the areas. In this sense, water and water edge areas, which are important for their resource values, are also important landscape values for recreational activities. From these landscapes values, creeks and the surrounding areas have become a major source of daily life in the past, as well as a major attraction for people's leisure time. However, their qualities and quantities must be sufficient to enable these areas to be used effectively in a recreational sense and to be able to fulfill their recreational functions. The purpose of the study is to identify the recreational use of the water-based activities and identify effective service areas in dense urbanization zones along the creek and green spaces around them. For this purpose, the study was carried out in the vicinity of Nilufer Creek in Bursa. The study area and its immediate surroundings are in the boundaries of Osmangazi and Nilufer districts. The study was carried out in the green spaces along the creek with an individual interaction of 17.930m. These areas are Hudavendigar Urban Park, Atatürk Urban Forest, Bursa Zoo, Soganlı Botanical Park, Mihrapli Park, Nilufer Valley Park. In the first phase of the study, the efficiency zones of these locations were calculated according to international standards. 3200m of this locations are serving the city population and 800m are serving the district and neighborhood population. These calculations are processed on the digitized map by the AUTOCAD program using the satellite image. The efficiency zone of these green spaces in the city were calculated as 71.04 km². In the second phase of the study, water-based current activities were determined by evaluating the recreational potential of these green spaces, which are located along the Nilufer Creek, where efficiency zones have been identified. It has been determined that water-based activities are used intensively in Hudavendigar Urban Park and interacted with Nilufer Creek. Within the scope of effective zones for the study area, appropriate recreational planning proposals have been developed and water-based activities have been suggested.

Keywords: Bursa, efficiency zone, Nilufer Creek, recreation, water-based activities

Procedia PDF Downloads 161

Authors: Marizia Roberta Rasoanandrasana, Hery Lisy Tiana. Ranarijaona, Herintsitohaina Razakamanarivo, Eric Delaitre, Nandrianina Ramifehiarivo

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Madagascar is one of the producer’s countries of world's fine cocoa. Cocoa-based agroforestry systems (CBAS) plays a very important economic role for over 75% of the population in the north of Madagascar, the island's main cocoa-producing area. It is also viewed as a key factor in the deforestation of local protected areas. It is therefore urgent to establish a compromise between cocoa production and forest conservation in this region which is difficult due to a lack of accurate cocoa agro-systems data. In order to fill these gaps and to response to these socio-economic and environmental concerns, this study aims to describe CBAS by providing precise data on their characteristics and to establish a typology. To achieve this, 150 farms were surveyed and observed to characterize CBAS based on 11 agronomic and 6 socio-economic data. Also, 30 representative plots of CBAS among the 150 farms were inventoried for providing accurate ecological data (6 variables) as an additional data for the typology determination. The results showed that Madagascar’s CBAS systems are generally extensive and practiced by smallholders. Four types of cocoa-based agroforestry system were identified, with significant differences between the following variables: yield, planting age, cocoa density, density of associated trees, preceding crop, associated crops, Shannon-Wiener indices and species richness in the upper stratum. Type 1 is characterized by old systems (>45 years) with low crop density (425 cocoa trees/ha), installed after conversion of crops other than coffee (> 50%) and giving low yields (427 kg/ha/year). Type 2 consists of simple agroforestry systems (no associated crop 0%), fairly young (20 years) with low density of associated trees (77 trees/ha) and low species diversity (H'=1.17). Type 3 is characterized by high crop density (778 trees/ha and 175 trees/ha for cocoa and associated trees respectively) and a medium level of species diversity (H'=1.74, 8 species). Type 4 is particularly characterized by orchard regeneration method involving replanting and tree lopping (100%). Analysis of the potential of these four types has identified Type 4 as a promising practice for sustainable agriculture.

Keywords: conservation, practices, productivity, protect areas, smallholder, trade-off, typology

Procedia PDF Downloads 117

Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Lalit Kumar, Rashid Al Shidi

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Phoenix dactylifera (date palm) is a major crop in many middle-eastern countries, including Oman. The Dubas bug Ommatissus lybicus is the main pest that affects date palm crops. However not all plantations are infested. It is still uncertain why some plantations get infested while others are not. This research investigated whether tree density and the system of planting (random versus systematic) had any relationship with infestation and levels of infestation. Remote Sensing and Geographic Information Systems were used to determine the density of trees (number of trees per unit area) while infestation levels were determined by manual counting of insects on 40 leaflets from two fronds on each tree, with a total of 20-60 trees in each village. The infestation was recorded as the average number of insects per leaflet. For tree density estimation, WorldView-3 scenes, with eight bands and 2m spatial resolution, were used. The Local maxima method, which depends on locating of the pixel of highest brightness inside a certain exploration window, was used to identify the trees in the image and delineating individual trees. This information was then used to determine whether the plantation was random or systematic. The ordinary least square regression (OLS) was used to test the global correlation between tree density and infestation level and the Geographic Weight Regression (GWR) was used to find the local spatial relationship. The accuracy of detecting trees varied from 83–99% in agricultural lands with systematic planting patterns to 50–70% in natural forest areas. Results revealed that the density of the trees in most of the villages was higher than the recommended planting number (120–125 trees/hectare). For infestation correlations, the GWR model showed a good positive significant relationship between infestation and tree density in the spring season with R² = 0.60 and medium positive significant relationship in the autumn season, with R² = 0.30. In contrast, the OLS model results showed a weaker positive significant relationship in the spring season with R² = 0.02, p < 0.05 and insignificant relationship in the autumn season with R² = 0.01, p > 0.05. The results showed a positive correlation between infestation and tree density, which suggests the infestation severity increased as the density of date palm trees increased. The correlation result showed that the density alone was responsible for about 60% of the increase in the infestation. This information can be used by the relevant authorities to better control infestations as well as to manage their pesticide spraying programs.

Keywords: dubas bug, date palm, tree density, infestation levels

Procedia PDF Downloads 193

Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

Procedia PDF Downloads 153