Search results for: forest biodiversity

Authors: Gadinga Walter Forje, Martin Ngankam Tchamba, Nyong Princely Awazi, Barnabas Neba Nfornka

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Ecotourism is viewed as a double edge sword for the enhancement of conservation and local livelihood within a protected landscape. The Campo Ma’an National Park (CMNP) adopted ecotourism in its management plan as a strategic axis for better management of the park. The growing importance of ecotourism as a strategy for the sustainable management of CMNP and its environs requires adequate information to bolster the sector. This study was carried out between November 2018 and September 2021, with the main objective to contribute to the sustainable management of the CMNP through suggestions for enhancing the capacity of ecotourism in and around the park. More specifically, the study aimed at; 1) Analyse the governance of ecotourism in the CMNP and its surrounding; 2) Assessing the impact of ecotourism on local livelihood around the CMNP; 3) Evaluating the contribution of ecotourism to biodiversity conservation in and around the CMNP; 4) Evaluate the determinants of ecotourism possibilities in achieving sustainable livelihood and biodiversity conservation in and around the CMNP. Data were collected from both primary and secondary sources. Primary data were obtained from household surveys (N=124), focus group discussions (N=8), and key informant interviews (N=16). Data collected were coded and imputed into SPSS (version 19.0) software and Microsoft Excel spreadsheet for both quantitative and qualitative analysis. Findings from the Chi-square test revealed overall poor ecotourism governance in and around the CMNP, with benefit sharing (X2 = 122.774, p <0.01) and conflict management (X2 = 90.839, p<0.01) viewed to be very poor. For the majority of the local population sampled, 65% think ecotourism does not contribute to local livelihood around CMNP. The main factors influencing the impact of ecotourism around the CMNP on the local population’s livelihood were gender (logistic regression (β) = 1.218; p = 0.000); and level of education (logistic regression (β) = 0.442; p = 0.000). Furthermore, 55.6% of the local population investigated believed ecotourism activities do not contribute to the biodiversity conservation of CMNP. Spearman correlation between socio-economic variables and ecotourism impact on biodiversity conservation indicated relationships with gender (r = 0.200, p = 0.032), main occupation (r = 0.300 p = 0.012), time spent in the community (r = 0.287 p = 0.017), and number of children (r =-0.286 p = 0.018). Variables affecting ecotourism impact on biodiversity conservation were age (logistic regression (β) = -0.683; p = 0.037) and gender (logistic regression (β) = 0.917; p = 0.045). This study recommends the development of ecotourism-friendly policies that can accelerate Public Private Partnership for the sustainable management of the CMNP as a commitment toward good governance. It also recommends the development of gender-sensitive ecotourism packages, with fair opportunities for rural women and more parity in benefit sharing to improve livelihood and contribute more to biodiversity conservation in and around the Park.

Keywords: biodiversity conservation, Campo Ma’an national park, ecotourism, ecotourism governance, rural livelihoods, protected area management

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Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Najoua El Hajjaji El Idrissi, Necip Gokhan Kasapoglu

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Polarimetric Synthetic Aperture Radar-based imaging is a powerful technique used for earth observation and classification of surfaces. Forest evolution has been one of the vital areas of attention for the remote sensing experts. The information about forest areas can be achieved by remote sensing, whether by using active radars or optical instruments. However, due to several weather constraints, such as cloud cover, limited information can be recovered using optical data and for that reason, Polarimetric Synthetic Aperture Radar (PolSAR) is used as a powerful tool for forestry inventory. In this [14paper, we applied support vector machine (SVM) and Mahalanobis distance to the fully polarimetric AIRSAR P, L, C-bands data from the Nezer forest areas, the classification is based in the separation of different tree ages. The classification results were evaluated and the results show that the SVM performs better than the Mahalanobis distance and SVM achieves approximately 75% accuracy. This result proves that SVM classification can be used as a useful method to evaluate fully polarimetric SAR data with sufficient value of accuracy.

Keywords: classification, synthetic aperture radar, SAR polarimetry, support vector machine, mahalanobis distance

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Authors: Mercy Chepkirui, Paul Orina, Robin Abell, Leonard Akwany, Tonny Orina, Mercy Matuma, Rasowo Joseph

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Lake jipe, a shared water resource between Kenya and Tanzania located at the East African Coast, is under multiple pressures. The lake has receded from 30Km2 to 27.32Km2 due to prolonged dry spells and intensified water abstraction for irrigation and re-route to Mungu ya Nyumba Dam in Tanzania. Agricultural activities have significantly (90%) contributed to the lake levels decline and further affected the lakes’ aquatic biodiversity. Among the most affected are the commercially important endemic fish species of the lake, of which Oreochromis jipe has experienced the greatest decline. Overfishing, use of illegal unreported and unregulated fishing gears, intensified fishing along protected fish breeding areas as well as poor management and uncoordinated conservation efforts have significantly contributed to the decline of fish catches from 348 kg of O. jipe in 2016 to 90 kg daily catches in 2022. Therefore, the lake is on the verge of extinction if no action is taken. This calls for awareness of the significance of the L. Jipe ecosystems and its immediate and long-term benefits. Further, there is a need to revive alternative economic activities, including aquaculture and sustainable agriculture, to offer alternative livelihood to local communities.

Keywords: biodiversity, ecosystem, conservation, fisheries

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Zouhaier Nasr, Mohamed Nouri

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The increase in greenhouse gases since the pre-industrial period is a real threat to disrupting the balance of marine and terrestrial ecosystems. Along with the oceans, forest soils are considered to be the planet's second-largest carbon sink. North African forests have been subject to alarming degradation for several decades. The objective of this investigation is to determine and quantify the effect of thinning practiced in pine forests in northern Tunisia on the storage of organic carbon in the trees and in the soil. The plot planted in 1989 underwent thinning in 2005 on to plots; the density is therefore 1600 trees/ha in control and 400 trees/ha in thinning. Direct dendrometric measurements (diameter, height, branches, stem) were taken. In the soil part, six profiles of 1m / 1m / 1m were used for soil and root samples and biomass and organic matter measurements. The measurements obtained were statistically processed by appropriate software. The results clearly indicate that thinning improves tree growth, so the diameter increased from 24.3 cm to 30.1 cm. Carbon storage in the trunks was 35% more and 25% for the whole tree. At ground level, the thinned plot shows a slight increase in soil organic matter and quantity of carbon per tree, exceeding the control by 10 to 25%.

Keywords: forest, soil, carbon, climate change, Tunisia

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Authors: Bedilu Tafesse

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The diversity and ecological analysis of vascular epiphytes was studied in Gera Forest in southwestern Ethiopia at altitudes between 1600 and 2400 m.a.s.l. A total area of 4.5 ha was surveyed in coffee and non-coffee forest vegetation. Fifty sampling plots, each 30 m x 30 m (900 m2), were used for the purpose of data collection. A total of 59 species of vascular epiphytes were recorded, of which 34 (59%) were holo epiphytes, two (4%) were hemi epiphytes and 22 (37%) species were accidental vascular epiphytes. To study the altitudinal distribution of vascular epiphytes, altitudes were classified into higher >2000, middle 1800-2000 and lower 1600-1800 m.a.s.l. According to Shannon-Wiener Index (H/= 3.411) of alpha diversity the epiphyte community in the study area is medium. There was a statistically significant difference between host bark type and epiphyte richness as determined by one-way ANOVA p = 0.001 < 0.05. The post-hoc test shows that there is significant difference of vascular epiphytes richness between smooth bark with rough, flack and corky bark (P =0.001< 0.05), as well as rough and cork bark (p =0.43 <0.05). However, between rough and flack bark (p = 0.753 > 0.05) and between flack and corky bark (p = 0.854 > 0.05) no significant difference of epiphyte abundance was observed. Rough bark had 38%, corky 26%, flack 25%, and only 11% vascular epiphytes abundance occurred on smooth bark. The regression correlation test, (R2 = 0.773, p = 0.0001 < 0.05), showed that the number of species of vascular epiphytes and host DBH size are positively correlated. The regression correlation test (R2 = 0.28, p = 0.0001 < 0.05), showed that the number of species and host tree height positively correlated. The host tree preference of vascular epiphytes was recorded for only Vittaria volkensii species hosted on Syzygium guineense trees. The result of similarity analysis indicated that Gera Forest showed the highest vascular epiphytic similarity (0.35) with Yayu Forest and shared the least vascular epiphytic similarity (0.295) with Harenna Forest. It was concluded that horizontal stems and branches, large and rough, flack and corky bark type trees are more suitable for vascular epiphytes seedling attachments and growth. Conservation and protection of these phorophytes are important for the survival of vascular epiphytes and increase their ecological importance.

Keywords: accidental epiphytes, hemiepiphyte, holoepiphyte, phorophyte

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Authors: Sakshi Gupta, Kavita Sardana

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Management of a forest catchment involves diverse dimensions, multiple stakeholders, and conflicting interests, primarily due to the wide variety of valuable ecosystem services offered by it. Often, the coordination among different levels of formal institutions governing the catchment, local communities, as well as societal norms, taboos, customs and practices, happens to be amiss, leading to conflicting policy interventions which prove detrimental for such resources. In the case of Ala Catchment, which is a protected forest located at a distance of 9 km North-East of the town of Dalhousie, within district Chamba of Himachal Pradesh, India, and serves as one of the primary sources of public water supply for the downstream town of Dalhousie and nearby areas, several policy measures have been adopted for the restoration of the forest catchment, as well as for the improvement of public water supply. These catchment forest restoration measures include; the installation of a fence along the perimeter of the catchment, plantation of trees in the empty patches of the forest, construction of check dams, contour trenches, contour bunds, issuance of grazing permits, and installation of check posts to keep track of trespassers. While the measures adopted to address the acute shortage of public water supply in the Dalhousie region include; building and maintenance of large capacity water storage tanks, laying of pipelines, expanding public water distribution infrastructure to include water sources other than Ala Catchment Forest and introducing of five new water supply schemes for drinking water as well as irrigation. However, despite these policy measures, the degradation of the Ala catchment and acute shortage of water supply continue to distress the region. This study attempts to conduct an institutional analysis to assess the impact of policy measures for the restoration of the Ala Catchment in the Chamba district of Himachal Pradesh in India. For this purpose, the theoretical framework of Ostrom’s Institutional Assessment and Development (IAD) Framework was used. Snowball sampling was used to conduct private interviews and focused group discussions. A semi-structured questionnaire was administered to interview a total of 184 respondents across stakeholders from both formal and informal institutions. The central hypothesis of the study is that the interplay of formal and informal institutions facilitates the implementation of policy measures for ameliorating Ala Catchment, in turn improving the livelihood of people depending on this forest catchment for direct and indirect benefits. The findings of the study suggest that leakages in the successful implementation of policy measures occur at several nodes of decision-making, which adversely impact the catchment and the ecosystem services provided by it. Some of the key reasons diagnosed by the immediate analysis include; ad-hoc assignment of property rights, rise in tourist inflow increasing the pressures on water demand, illegal trespassing by local and nomadic pastoral communities for grazing and unlawful extraction of forest products, and rent-seeking by a few influential formal institutions. Consequently, it is indicated that the interplay of formal and informal institutions may be obscuring the consequentiality of the policy measures on the restoration of the catchment.

Keywords: catchment forest restoration, institutional analysis and development framework, institutional interplay, protected forest, water supply management

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: Alma Mendoza-Ponce, Rogelio Corona-Núñez, Florian Kraxner

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Mexico is a megadiverse country and it has nearly halved its natural vegetation in the last century due to agricultural and livestock expansion. Impacts of land use cover change and climate change are unevenly distributed and spatial prioritization to minimize the affectations on biodiversity is crucial. Global and national efforts for prioritizing biodiversity conservation show that ~33% to 45% of Mexico should be protected. The width of these targets makes difficult to lead resources. We use a framework based on vulnerability and irreplaceability to prioritize conservation efforts in Mexico. Vulnerability considered exposure, sensitivity and adaptive capacity under two scenarios (business as usual, BAU based, on the SSP2 and RCP 4.5 and a Green scenario, based on the SSP1 and the RCP 2.6). Exposure to land use is the magnitude of change from natural vegetation to anthropogenic covers while exposure to climate change is the difference between current and future values for both scenarios. Sensitivity was considered as the number of endemic species of terrestrial vertebrates which are critically endangered and endangered. Adaptive capacity is used as the ration between the percentage of converted area (natural to anthropogenic) and the percentage of protected area at municipality level. The results suggest that by 2050, between 11.6 and 13.9% of Mexico show vulnerability ≥ 50%, and by 2070, between 12.0 and 14.8%, in the Green and BAU scenario, respectively. From an ecosystem perspective cloud forests, followed by tropical dry forests, natural grasslands and temperate forests will be the most vulnerable (≥ 50%). Amphibians are the most threatened vertebrates; 62% of the endemic amphibians are critically endangered or endangered while 39%, 12% and 9% of the mammals, birds, and reptiles, respectively. However, the distribution of these amphibians counts for only 3.3% of the country, while mammals, birds, and reptiles in these categories represent 10%, 16% and 29% of Mexico. There are 5 municipalities out of the 2,457 that Mexico has that represent 31% of the most vulnerable areas (70%).These municipalities account for 0.05% of Mexico. This multiscale approach can be used to address resources to conservation targets as ecosystems, municipalities or species considering land use cover change, climate change and biodiversity uniqueness.

Keywords: biodiversity, climate change, land use change, Mexico, vulnerability

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Authors: Margareta Rahayuningsih, Nugroho Edi K., Siti Alimah

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Wreathed Hornbill (Rhyticeros undulatus) is the one of hornbill species (Family: Bucerotidae) that found on Mount Ungaran. In the preservation or planning in situ conservation of Wreathed Hornbill require the habitat condition data. The objective of the research was to determine the land cover change on Mount Ungaran using satellite image data and GIS. Based on the land cover data on 1999-2009 the research showed that the primer forest on Mount Ungaran was decreased almost 50%, while the seconder forest, tea and coffee plantation, and the settlement were increased.

Keywords: GIS, Mount Ungaran, threatened habitat, Wreathed Hornbill (Rhyticeros undulatus)

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Authors: Albert Kwabena Osei Konadu

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Pterocarpus erinaceus, also known as Rosewood, is tropical wood, endemic in forest savannah transition zones within the middle and northern portion of Ghana. Its economic viability has made it increasingly popular and in high demand, leading to widespread conservation concerns. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective, sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: convention on international trade in endangered species, cubic volume formula, forest transition savannah zones, pterocarpus erinaceus, smallian’s volume formula, tree information form

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Authors: Titilope F. Onaolapo, Christiana A. Breed, Maya Pasgaard, Kristine E. Jensen, Peta Brom

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In the face of fast-growing urbanization in most of the world's developing countries, there is a need to understand and address the risk and consequences involved in the indiscriminate use of urban green space. Tshwane city in South Africa has the potential to become one of the world's top biodiversity cities as South Africa is ranked one of the mega countries in biodiversity conservation, and Tshwane metropolitan municipality is the city with the wealthiest biodiversity with grassland biomes. In this study, we focus on the potentials and challenges of urban green transitioning from the Global South perspective with Tshwane city as the case study. We also address the issue of management conflicts that have resulted in informal and illegal activities in and around green spaces, with consequences such as land degradation, loss of livelihoods and biodiversity, and socio-ecological imbalances. A desk study review of eight policy frameworks related to green urban planning and development was done based on four GI principles: multifunctionality, connectivity, interdisciplinary and social inclusion. We interviewed 15 key informants in related departments in the city and administered 200 survey questionnaires among residents. We also had several workshops the other researchers and experts on biodiversity and ecosystem. We found out there is no specific document dedicated to green space management, and where green infrastructure was mentioned, it was focused on as an approach to climate mitigation and adaptation. Also, residents perceive green and open spaces as extra land that could be developed at will. We demonstrated the use of collaborative learning approaches in ecological and development research and the tying research to the existing frameworks, programs, and strategies. Based on this understanding. We outlined the need to incorporate principles of green infrastructure in policy frameworks on spatial planning and environmental development. Furthermore, we develop a model for co-management of green infrastructures by stakeholders, such as residents, developers, policymakers, and decision-makers, to maximize benefits. Our collaborative, interdisciplinary projects pursue SDG multifunctionality of goals 11 and 15 by simultaneously addressing issues around Sustainable Cities and Communities, Climate Action, Life on Land, and Strong Institutions, and halt and reverse land degradation and biodiversity.

Keywords: governance, green infrastructure, South Africa, sustainable development, urban planning, Tshwane

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Chevonne Reynolds, Robert J. Fletcher, Jr, Celine M. Carneiro, Nicole Jennings, Alison Ke, Michael C. LaScaleia, Mbhekeni B. Lukhele, Mnqobi L. Mamba, Muzi D. Sibiya, James D. Austin, Cebisile N. Magagula, Themba’alilahlwa Mahlaba, Ara Monadjem, Samantha M. Wisely, Robert A. McCleery

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A key challenge for the developing world is reconciling biodiversity conservation with the growing demand for food. In these regions, agriculture is typically interspersed among other land-uses creating heterogeneous landscapes. A primary hypothesis for promoting biodiversity in agricultural landscapes is the habitat heterogeneity hypothesis. While there is evidence that landscape heterogeneity positively influences biodiversity, the application of this hypothesis is hindered by a need to determine which components of landscape heterogeneity drive these effects and at what spatial scale(s). Additionally, whether diverse taxonomic groups are similarly affected is central for determining the applicability of this hypothesis as a general conservation strategy in agricultural mosaics. Two major components of landscape heterogeneity are compositional and configurational heterogeneity. Disentangling the roles of each component is important for biodiversity conservation because each represents different mechanisms underpinning variation in biodiversity. We identified a priori independent gradients of compositional and configurational landscape heterogeneity within an extensive agricultural mosaic in north-eastern Swaziland. We then tested how bird, dung beetle, ant and meso-carnivore diversity responded to compositional and configurational heterogeneity across six different spatial scales. To determine if a general trend could be observed across multiple taxa, we also tested which component and spatial scale was most influential across all taxonomic groups combined, Compositional, not configurational, heterogeneity explained diversity in each taxonomic group, with the exception of meso-carnivores. Bird and ant diversity was positively correlated with compositional heterogeneity at fine spatial scales < 1000 m, whilst dung beetle diversity was negatively correlated to compositional heterogeneity at broader spatial scales > 1500 m. Importantly, because of these contrasting effects across taxa, there was no effect of either component of heterogeneity on the combined taxonomic diversity at any spatial scale. The contrasting responses across taxonomic groups exemplify the difficulty in implementing effective conservation strategies that meet the requirements of diverse taxa. To promote diverse communities across a range of taxa, conservation strategies must be multi-scaled and may involve different strategies at varying scales to offset the contrasting influences of compositional heterogeneity. A diversity of strategies are likely key to conserving biodiversity in agricultural mosaics, and we have demonstrated that a landscape management strategy that only manages for heterogeneity at one particular scale will likely fall short of management objectives.

Keywords: agriculture, biodiversity, composition, configuration, heterogeneity

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

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Authors: A B M Enamol Hassan

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The forest storing up in Bangladesh is of deep concern to policy analysts because of increasing encroachment that results in deforestation and degradation of the ecosystem. To address these problems, forest-dependent people, as responsible for encroachment, could be involved in the co-management process along with other local stakeholders through a participatory approach. On the basis of this premise, this paper conceptualizes and empirically assesses the integration of all stakeholders in the co-management process through two lenses such as participation and collaboration. The study also analyzed the issues of sustainability in local communities along with examining constraints that limit the processes of integration. The study used a qualitative research method, which included face-to-face interviews with semi-structured questionnaires and field notes following the purposive sampling technique focusing on Comilla Sadar South Upazila (CSSU), Bangladesh. The findings of this paper reveal beneficiaries, Bangladesh Forest Department (BFD) and Union Parishad (UP), come together as leading actors, while NGOs and business entrepreneurs are ignored in the co-management process of social forestry. However, integrated management contributes to the strength of community sustainability, although it has some major limitations causing the matter of concerns among the local communities and policy analysts.

Keywords: integration, participation, collaboration, stakeholders, community sustainability

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Authors: Herbert Ntuli, Edwin Muchapondwa

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This study used a sample of 336 households and community level data from 30 communities around the Gonarezhou National Park in Zimbabwe to analyse the association between ability to self-organize or cooperation and institutions on one hand and the relationship between success of biodiversity outcomes and cooperation on the other hand. Using both the ordinary least squares and instrumental variables estimation with heteroskedasticity-based instruments, our results confirmed that sound institutions are indeed an important ingredient for cooperation in the respective communities and cooperation positively and significantly affects biodiversity outcomes. Group size, community level trust, the number of stakeholders and punishment were found to be important variables explaining cooperation. From a policy perspective, our results show that external enforcement of rules and regulations does not necessarily translate into sound ecological outcomes but better outcomes are attainable when punishment is rather endogenized by local communities. This seems to suggest that communities should rather be supported in such a way that robust institutions that are tailor made to suit the needs of local condition will emerge that will in turn facilitate good environmental husbandry. Cooperation, training, benefits, distance from the nearest urban canter, distance from the fence, social capital average age of household head, fence and information sharing were found to be very important variables explaining the success of biodiversity outcomes ceteris paribus. Government programmes should target capacity building in terms of institutional capacity and skills development in order to have a positive impact on biodiversity. Hence, the role of stakeholders (e.g., NGOs) in capacity building and government effort should complement each other to ensure that the necessary resources are mobilized and all communities receive the necessary training and resources.

Keywords: institutions, self-organize, common pool resources, wildlife, conservation, Zimbabwe

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Authors: Damian Czubak

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The Białowieża Forest is a very valuable natural area, included in the World Natural Heritage at UNESCO, where, due to infestation by the bark beetle (Ips typographus), norway spruce (Picea abies) have deteriorated. This catastrophic scenario led to an increase in fire danger. This was due to the occurrence of large amounts of dead wood and grass cover, as light penetrated to the bottom of the stands. These factors in a dry state are materials that favour the possibility of fire and the rapid spread of fire. One of the objectives of the study was to monitor the quantitative and qualitative changes of combustible material on the permanent decay plots of spruce stands from 2012-2022. In addition, the size of the area with highly flammable vegetation was monitored and a classification of the stands of the Białowieża Forest by flammability classes was made. The key factor that determines the potential fire hazard of a forest is combustible material. Primarily its type, quantity, moisture content, size and spatial structure. Based on the inventory data on the areas of forest districts in the Białowieża Forest, the average fire load and its changes over the years were calculated. The analysis was carried out taking into account the changes in the health status of the stands and sanitary operations. The quantitative and qualitative assessment of fallen timber and fire load of ground cover used the results of the 2019 and 2021 inventories. Approximately 9,000 circular plots were used for the study. An assessment was made of the amount of potential fuel, understood as ground cover vegetation and dead wood debris. In addition, monitoring of areas with vegetation that poses a high fire risk was conducted using data from 2019 and 2021. All sub-areas were inventoried where vegetation posing a specific fire hazard represented at least 10% of the area with species characteristic of that cover. In addition to the size of the area with fire-prone vegetation, a very important element is the size of the fire load on the indicated plots. On representative plots, the biomass of the land cover was measured on an area of 10 m2 and then the amount of biomass of each component was determined. The resulting element of variability of ground covers in stands was their flammability classification. The classification developed made it possible to track changes in the flammability classes of stands over the period covered by the measurements.

Keywords: classification, combustible material, flammable vegetation, Norway spruce

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Authors: Sudabe Amini, Jamasb Nozari, Somaye Rahimi

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Bark beetles are one of the most destructive groups of pests in the forest and green space. Mediterranean pine Engraver Orthotomicus erosus (Wollston) is the dominant species in the pine forests of Iran. Pine forests are considered a crucial region in the world and need high protection. Although there is no effective control method, mass trapping is the most common method to suppress the bark beetle population. Due to this, from 2018-to 2020, a survey was conducted on bark beetles mass trapping by using two kinds of traps, including pheromone and tree trap. These traps were evaluated in 10 different sites of pine forests. The statistical results proved that significant differences between the pheromone trap and tree trap were observed. It confirmed that the pheromone trap attracted more beetles than the tree trap. The results of this study suggest that the most effective and applicable method in bark beetle’s management of pines forest is using a pheromone trap that suppresses and maintains bark beetle’s population at an economic level, although tree traps attract bark beetles too. In the future, using tree-pheromone traps, which would synergist attraction of more bark beetles, is recommended.

Keywords: bark beetle, pines forest, Orthotomicus erosus, pheromone trap, tree trap

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Juang R. Matangaran, Erianto I. Putra, Iis Diatin, Muhammad Mujahid, Qi Adlan

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Industrial plantation forest is the producer of logs in Indonesia. Several companies of industrial plantation forest have been successfully planted with fast-growing species, and it entered their annual harvesting period. Heavy machines such as forwarders are used in timber harvesting to extract logs from stump to landing site. The negative impact of using such machines are loss of topsoil and soil compaction. Compacted soil is considered unfavorable for plant growth. The research objectives were to analyze the soil bulk density, rut, and cone index of the soil caused by a forwarder passes, to analyze the relation between several times of forwarder passes to the increase of soil bulk density. A Valmet forwarder was used in this research. Soil bulk density at soil surface and cone index from the soil surface to the 50 cm depth of soil were measured at the harvested area. The result showed that soil bulk density increase with the increase of the Valmet forwarder passes. Maximum soil bulk density occurred after 5 times forwarder Valmet passed. The cone index tended to increase from the surface until 50 cm depth of soil. Rut formed and high soil bulk density indicated the soil compaction occurred by the forwarder operation.

Keywords: bulk density, forwarder Valmet, plantation forest, soil compaction, timber harvesting

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Authors: L. Salvati, D. Smiraglia, S. Bajocco, M. Munafò

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This paper focuses on Land Use and Land Cover Changes (LULCC) occurred in the urban coastal regions of the Mediterranean basin in the last thirty years. LULCC were assessed diachronically (1975-2006) in two urban areas, Rome (Italy) and Athens (Greece), by using CORINE land cover maps. In strictly coastal territories a persistent growth of built-up areas at the expenses of both agricultural and forest land uses was found. On the contrary, a different pattern was observed in the surrounding inland areas, where a high conversion rate of the agricultural land uses to both urban and forest land uses was recorded. The impact of city growth on the complex pattern of coastal LULCC is finally discussed.

Keywords: land use changes, coastal region, Rome prefecture, Attica, southern Europe

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Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: M. S. Sarkar, J. A. Johnson, S. Sen, G. K. Saha, K. Ramesh

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There is growing recognition of several important roles played by tigers for maintaining sustainable biodiversity at diverse ecosystems in South and South-East Asia. Only <3200 individuals are left in the wild because of poaching and habitat loss. Thus, restoring wild population is an emerging as well as important conservation initiative, but such efforts still remain challenging due to their elusive and solitary behavior. After careful translocation of few individuals, how reintroduced individuals colonize into suitable habitat and achieve stable stage population through reproduction is vital information for forest managers and policy makers of its 13 distribution range countries. Four wild and two captive radio collared tigers were reintroduced at Panna Tiger Reserve, Madhya-pradesh, India during 2009-2014. We critically examined their settlement behavior and population growth over the period. Results from long term telemetry data showed that male explored larger areas rapidly in short time span, while females explored small area in long time period and with significant high rate of movement in both sexes during exploratory period. Significant difference in home range sizes of tigers were observed in exploratory and settlement period. Though all reintroduced tigers preferred densely vegetated undisturbed forest patches within the core area of tiger reserve, a niche based k select analysis showed that individual variation in habitat selection was prominent among reintroduced tigers. Total 18 litter of >42 known cubs were born with low mortality rate, high maternity rate, high observed growth rate and short generation time in both the sexes. The population achieved its carrying capacity in a very short time span, marking success of this current tiger conservation programme. Our study information could provide significant insights on the tiger biology of translocated tigers with implication for future conservation strategies that consider translocation based recovery in their range countries.

Keywords: reintroduction, tiger, home range, demography

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Kishor Prasad Bhatta, Suman Ghimire, Durga Prasad Joshi

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Invasive Alien Species (IAS) are considered waste forest resources in Nepal. The rapid expansion of IAS is one of the nine main drivers of forest degradation, though the extent and distribution of this species are not well known. Further, the knowledge of the impact of IAS removal on forest plant diversity is hardly known, and the possibilities of income generation from them at the grass-root communities are rarely documented. Systematic sampling of 1% with nested circular plots of 500 square meters was performed in IAS removed and non-removed area, each of 30 hectares in Udayapur Community Forest User Group (CFUG), Chitwan, central Nepal to observe whether the removal of IAS contributed to an increase in plant diversity. In addition, ten entrepreneurs of Udaypur CFUG, involved in the charcoal production, briquette making and marketing were interviewed and interacted as well as their record keeping booklets were reviewed to understand if the charcoal production contributed to their income and employment. The average annual precipitation and temperature of the study area is 2100 mm and 34 degree Celsius respectively with Shorea robusta as main tree species and Eupatorium odoratum as dominant IAS. All the interviewed households were from the ̔below-poverty-line’ category as per Community Forestry Guidelines. A higher Shannon-Weiner plant diversity index at regeneration level was observed in IAS removed areas (2.43) than in control site (1.95). Furthermore, the number of tree seedlings and saplings in the IAS harvested blocks were significantly higher (p < 0.005) compared to the unharvested one. The sale of charcoal produced through the pyrolysis of IAS in ̔ Bio-energy kilns’ contributed for an average increased income of 30.95 % (Nepalese rupees 31,000) of the involved households. Despite above factors, some operational policy hurdles related to charcoal transport and taxation existed at field level. This study suggests that plant diversity could be increased through the removal of IAS, and considerable economic benefits could be achieved if charcoal is substantially produced and utilized.

Keywords: briquette, economic benefits, pyrolysis, regeneration

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Authors: Dali Nikolaishvili, Nino Khareba, Mariam Tsitsagi

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Tbilisi has been a capital of Georgia since the 5ᵗʰ century. City area was covered by forest in historical past. Nowadays the situation has been changing dramatically. Dozens of problems are caused by damages/destruction of green cover and solution, at one glance, seems to be uncomplicated (planting trees and creating green quarters), but on the other hand, according to the increasing tendency, the built up of areas still remains unsolved. Finding out the ways to overcome such obstacles is important even for protecting the health of society. Making of Retrospective cartography of the forest area of Tbilisi with use of GIS technology and remote sensing was the main aim of the research. Research about the dynamic of forest-cover in Tbilisi and its surroundings included the following steps: assessment of the dynamic of forest in Tbilisi and its surroundings. The survey was mainly based on the retrospective mapping method. Using of GIS technology, studying, comparing and identifying the narrative sources was the next step. And the last one was analyzed of the changes from the 80s to the present days on the basis of decryption of remotely sensed images. After creating a unified cartographic basis, the mapping and plans of different periods have been linked to this geodatabase. Data about green parks, individual old plants existing in the private yards and respondents' Information (according to a questionnaire created in advance) was added to the basic database, the general plan of Tbilisi and Scientific works as well. On the basis of analysis of historic, including cartographic sources, forest-cover maps for different periods of time were made. In addition, was made the catalog of individual green parks (location, area, typical composition, name and so on), which was the basis of creating several thematic maps. Areas with a high rate of green area degradation were identified. Several maps depicting the dynamics of forest cover of Tbilisi were created and analyzed. The methods of linking the data of the old cartographic sources to the modern basis were developed too, the result of which may be used in Urban Planning of Tbilisi. Understanding, perceiving and analyzing the real condition of green cover in Tbilisi and its problems, in turn, will help to take appropriate measures for the maintenance of ancient plants, to develop forests and to plan properly parks, squares, and recreational sites. Because the healthy environment is the main condition of human health and implies to the rational development of the city.

Keywords: catalogue of green area, GIS, historical cartography, cartography, remote sensing, Tbilisi

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Authors: Albert Kwabena Osei Konadu

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One of the endemic forest species of the savannah transition zones enlisted by the Convention of International Treaty for Endangered Species (CITES) in Appendix II is the Rosewood, also known as Pterocarpus erinaceus or Krayie. Its economic viability has made it increasingly popular and in high demand. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. The study was limited by the usage of regulators assigned volume as benchmark and also fraught with potential volume measurement error in the stacked billet scenario due to the existence of spaces within packed billets. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: cubic volume formula, smallian volume formula, pterocarpus erinaceus, tree information form, forest transition and savannah zones, harvested tree volume

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