Anthropogenic Effects in Tropical Forest Patches of Sipalay City Negros Occidental, Philippines

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Mae Flor G Posadas
Keyword(s):  
Tropical Forest ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Tropical Rain Forests ◽  
Forest Patches ◽  
Forest Reserves ◽  
Qualitative Approaches ◽  
Management And Development ◽  
Baseline Information ◽  
The Impact

Tropical rain forests are viable economic resources for people and their surrounding communities for they serve as sources of food and other materials. This descriptive research provides baseline information that describes and analyzes the socio-economic characteristics of human communities within the three forest patches of Sipalay City and the impact of their activities on these forest reserves. Quantitative and qualitative approaches were employed using survey, ethnobiology workshops, focus group discussions, and key informant interview methods to selected respondents living in these forests. Majority of the households that were natives and lived within the watershed reservation areas relied on farming and live below the poverty threshold due to lack of education, poor road network, and poor access to electricity and communication. Hence, forest areas were utilized in planting crops to support respondents’ meager incomes. Hunting, illegal logging, charcoal making, mining, dumping of garbage within the reservation, cutting of trees for firewood, kaingin/slash and burn system and human settlements were some of the anthropogenic activities that adversely affected the reservation and contributed to the decrease of vegetation, forest cover, and floral and faunal resources of Sipalay Forest Reserves. Given the situation, majority of the human communities living within the tropical forest were still willing to join programs that protect the remaining forest patches in Sipalay. Findings served as bases for identification of appropriate interventions for the management and development of the area.

scholarly journals Long Term Monitoring of Ghana’s Forest Reserves Using Google Earth Engine

2019 ◽  
Author(s):  
Jeff Dacosta Osei ◽  
S. A. Andam-Akorful ◽  
Edward Matthew Osei jnr
Keyword(s):  
Structural Changes ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Forest Monitoring ◽  
Forest Reserves ◽  
Deforestation Rate ◽  
Noaa Avhrr ◽  
Forestry Commission ◽  
Google Earth Engine

Farm activities continued sand winning operations and the allocation of plots of land to prospective developers in Ghana pose a serious threat to the forest covers and lifespan of the Forest and game reserves. With all the positive add ups to the country from forests, Ghana has lost more than 33.7%(equivalent to 2,500,000 hectares) of its forest, since the early 1990s between 2005 and 2010, the rate of deforestation in Ghana was estimated at 2.19% per annum; the sixth highest deforestation rate globally for that period. This shows how important forest monitoring can be to the forestry commission in Ghana. Despite the frameworks which have been developed to help Ghana to protect and restore its forest resources, inadequate monitoring systems remain a barrier to effective implementation. In this study, Google earth engine was used to map and analyze the structural changes of forest cover using JavaScript to query and compute Landsat, MODIS and NOAA AVHRR satellite imageries of the study area (Ghana) with spatial resolutions 30m, 250m and 7km respectively. A supervised classification was performed on three multi-temporal satellite imageries and a total of six major land use and land cover classes were identified and mapped. By using random Forest-classification technique, from 1985 to 2018 recorded by NOAA AVHRR, forest cover has decreased by 66% and 2000 to 2018 recorded by Landsat and MODIS 61% and 47% respectively. A decrease in the forest has been as a result of anthropogenic activities in Ghana. A change detection analysis was performed on these images and it was noted that Ghana is losing forest reserves in every 5years. Overlay of the reserved forest of the 2000 and the classified map of 2018 shows vegetation changed during 2000-2018 remarkably. Therefore, forest-related institutions like the Forestry Commission can employ and use this monitoring system on Google Earth Engine for processing satellite images particularly Landsat, MODIS and NOAA AVHRR for forest cover monitoring and analysis for fast, efficient and reliable results.

scholarly journals Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin

2020 ◽  
Vol 12 (4) ◽  
pp. 638 ◽  
Author(s):  
Koen Hufkens ◽  
Thalès de Haulleville ◽  
Elizabeth Kearsley ◽  
Kim Jacobsen ◽  
Hans Beeckman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Cover ◽  
Congo Basin ◽  
Spatial And Temporal Patterns ◽  
Smallholder Farming ◽  
Aboveground Carbon ◽  
Decadal Scale ◽  
Long Term Changes ◽  
The Impact

Given the impact of tropical forest disturbances on atmospheric carbon emissions, biodiversity, and ecosystem productivity, accurate long-term reporting of Land-Use and Land-Cover (LULC) change in the pre-satellite era (<1972) is an imperative. Here, we used a combination of historical (1958) aerial photography and contemporary remote sensing data to map long-term changes in the extent and structure of the tropical forest surrounding Yangambi (DR Congo) in the central Congo Basin. Our study leveraged structure-from-motion and a convolutional neural network-based LULC classifier, using synthetic landscape-based image augmentation to map historical forest cover across a large orthomosaic (~93,431 ha) geo-referenced to ~4.7 ± 4.3 m at submeter resolution. A comparison with contemporary LULC data showed a shift from previously highly regular industrial deforestation of large areas to discrete smallholder farming clearing, increasing landscape fragmentation and providing opportunties for substantial forest regrowth. We estimated aboveground carbon gains through reforestation to range from 811 to 1592 Gg C, partially offsetting historical deforestation (2416 Gg C), in our study area. Efforts to quantify long-term canopy texture changes and their link to aboveground carbon had limited to no success. Our analysis provides methods and insights into key spatial and temporal patterns of deforestation and reforestation at a multi-decadal scale, providing a historical context for past and ongoing forest research in the area.

scholarly journals Tropical Forest: A Potential Resource for Climate Change Mitigation in Ghana

2019 ◽  
pp. 435-442
Author(s):  
Emmanuel Amankwah
Keyword(s):  
Climate Change ◽  
Tropical Forest ◽  
Climate Change Mitigation ◽  
Anthropogenic Activities ◽  
Critical Role ◽  
Economic Benefits ◽  
The State ◽  
Potential Resource ◽  
The Impact ◽  
Change Mitigation

Climate variability and change has become a global phenomenon with many countries including Ghana working hard to mitigate the effect or develop strategies for adaptation.  However, tropical forest has been identified to have the capacity to mitigate the impact of climate change and improve the general environment. The forest plays a critical role in the climate system, hydrology and the carbon cycle, and provide livelihood for over 2.5 billion rural dwellers in developing countries. This article therefore highlights the importance of tropical forest as a potential resource for climate change mitigation and the need for policy makers, stakeholders and the general public to seriously adopt positive approach to the management of forest resources. The article was carried out through extensive review of literature, official reports and policy documents.  The paper outlines the threat of climate change, the state of Ghana’s forest and climate, and the role of the forest to mitigate climate change. It also highlights the socio-economic benefits of the forest in mitigating the changing climate. The documents reviewed showed that the state of Ghana’s forest has dwindled over the years through anthropogenic activities and the climate is also changing. It was also established that trees can remove substantial amount of CO2 from the atmosphere for storage. The paper concludes with recommendations for the preservation and regeneration of the tropical forest for the purpose of mitigating the effect of climate change in Ghana. 

scholarly journals Assessment of Landsat Based Deep-Learning Membership Analysis for Development of from–to Change Time Series in the Prairie Region of Canada from 1984 to 2018

2021 ◽  
Vol 13 (4) ◽  
pp. 634
Author(s):  
Darren Pouliot ◽  
Niloofar Alavi ◽  
Scott Wilson ◽  
Jason Duffe ◽  
Jon Pasher ◽  
...  
Keyword(s):  
Deep Learning ◽  
Land Cover ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Future Research ◽  
Habitat Amount ◽  
Subtle Change ◽  
Recent Climate ◽  
Land Covers ◽  
The Impact

The prairie region of Canada is a dynamically changing landscape in relation to past and present anthropogenic activities and recent climate change. Improving our understanding of the rate, timing, and distribution of landscape change is needed to determine the impact on wildlife populations and biodiversity, ultimately leading to better-informed management regarding requirements for habitat amount and its connectedness. In this research, we assessed the viability of an approach to detect from–to class changes designed to be scalable to the prairie region with the capacity for local refinement. It employed a deep-learning convolutional neural network to model general land covers and examined class memberships to identify land-cover conversions. For this implementation, eight land-cover categories were derived from the Agriculture and Agri-Food Canada Annual Space-Based Crop Inventory. Change was assessed in three study areas that contained different mixes of grassland, pasture, and forest cover. Results showed that the deep-learning method produced the highest accuracy across all classes relative to an implementation of random forest that included some first-order texture measures. Overall accuracy was 4% greater with the deep-learning classifier and class accuracies were more balanced. Evaluation of change accuracy suggested good performance for many conversions such as grassland to crop, forest to crop, water to dryland covers, and most bare/developed-related changes. Changes involving pasture with grassland or cropland were more difficult to detect due to spectral confusion among classes. Similarly, conversion to forests in some cases was poorly detected due to gradual and subtle change characteristics combined with confusion between forest, shrub, and croplands. The proposed framework involved several processing steps that can be explored to enhance the thematic content and accuracy for large regional implementation. Evaluation for understanding connectivity in natural land covers and related declines in species at risk is planned for future research.

scholarly journals A Bayesian Inference Procedure for structural characterization of Nigerian Tropical Forest

2021 ◽  
Author(s):  
SEHINDE AKINBIOLA ◽  
Ayobami Salami ◽  
Olusegun Awotoye
Keyword(s):  
Bayesian Inference ◽  
Tropical Forest ◽  
Wood Density ◽  
Structural Characteristics ◽  
Anthropogenic Activities ◽  
Carbon Stocks ◽  
Inference Procedure ◽  
Site Specific ◽  
Forest Reserves ◽  
Hardwood Species

Abstract The complexity of the tropical forest structure remains a challenge in forest physiognomy assessment, which is a crucial indicator of forest productivity with implications on the carbon cycle, biodiversity, and ecosystem services. The study assessed structural characteristics, described variability within forest stands, and estimated carbon stocks using simulation tools and tree modeling to focus on understanding and quantifying ecological relationships. The study discovered a site-specific wood density difference of 0.07g/cm3 compared with the generalized wood density for tropical forests by Food and Agricultural Organisation (FAO). Carbon stocks estimated with this site-specific wood density produced; 174 Mg Ca / ha-1, 155 Mg Ca / ha-1, and 78 Mg Ca / ha-1, respectively, from three sampled Forest Reserves. Furthermore, the result showed that the forest clusters' most productive layers (emergent and canopy layers) were predominantly hardwood species interspersed with softwood species with huge diameters. The height-diameter model indicated that although the height was a better predictor of the forest structural layer than the diameter, there was no clear margin for grouping species into layers in the region because of interspecies variations, temperature, and anthropogenic activities. The Bayesian Inference procedure provided a reliable approach for carbon stock estimate in the tropics with no legacy inventories.

scholarly journals Avian diversity in a fragmented landscape of central Indian forests (Bhopal Forest Circle)

2021 ◽  
Vol 13 (5) ◽  
pp. 18177-18188
Author(s):  
Amit Kumar ◽  
Yogesh Dubey ◽  
Advait Edgaonkar
Keyword(s):  
Species Richness ◽  
Anthropogenic Disturbance ◽  
Forest Cover ◽  
Community Dynamics ◽  
Bird Species ◽  
Vital Role ◽  
Fragmented Landscape ◽  
Forest Fragments ◽  
Forest Patches ◽  
The Impact

With increasing fragmentation of natural areas and a dramatic reduction of forest cover in several parts of the world, quantifying the impact of such changes on species richness and community dynamics has been a subject of much concern.  Therefore, this study intends to assess avifaunal biodiversity in fragmented forests.  Forest patches between the sizes of 10ha and 700ha were identified in Bhopal Forest Circle (BFC), which covers the Vindhyan plateau.  Forest patches were classified based on their size and degree of isolation.  A sample of 21 forest fragments was selected using proportional sampling.  Bird surveys were conducted using the point count method at each site.  Three replicates were taken at each site.  Avian species richness of each patch was calculated.  The results suggest that species richness is positively associated with the size of the forest patches.  Larger forest patches such as Binapur (166ha, Chao 1= 73), Sayar (107ha, Chao 1= 78) and Kalyanpura (133ha, Chao 1= 80) had relatively high species richness, except for patches including Narsinghgarh (393ha, Chao 1= 28) and Singota (184ha, Chao 1= 45) with high levels of anthropogenic disturbance.  Smaller forest patches were found to have fewer bird species, although small forest patches with lesser degrees of anthropogenic disturbance such as Lalghati (99ha, Chao 1 = 62), Lasudli (16ha, Chao 1 = 65), Ghot (36ha, Chao 1 = 53), and Nasipur (23ha, Chao 1 =52) were more diverse than other patches.  These patches were more protected due to being sacred groves (Lalghati and Lasudli) or under private ownership (Ghot and Nasipur).  A total of 131 bird species were recorded from all the sampled forest patches.  These results suggest that forest patches embedded in an agrarian landscape play a vital role in conserving biodiversity, hence conservation efforts should also be focused on these forest fragments.

scholarly journals Scénarii de Réduction des Emissions liées à la Déforestation et la Dégradation forestière en fonction du Niveau des Emissions de Référence pour les Forêts (NERF)

2021 ◽  
Vol 2 (1) ◽  
pp. 52-61
Author(s):  
EWOSSAKA Arsène ◽  
BOUNDZANGA Georges Claver ◽  
MIALOUNDAMA BAFOUETIKILA Gilles ◽  
NGONGOUYO Yvon ◽  
AKOUANGO Parisse
Keyword(s):  
Forest Cover ◽  
Clean Energy ◽  
Forest Degradation ◽  
Republic Of Congo ◽  
Développement Durable ◽  
Management And Development ◽  
The Republic ◽  
Development Approach ◽  
Changements Climatiques ◽  
The Impact

A country with very high forest cover and very low deforestation (High Forest Cover, Low Deforestation "HFLD"), the Republic of Congo presented its Forest Reference Emissions Level (NERF) in 2016. This NERF, approved by the United Nations Framework Convention on Climate Change (UNFCCC) in June 2017, is set at 35.5 million teCO2/year. It is organized around the estimate of historical emissions from 2000 to 2012 and future emissions from 2015 to 2020, related to Deforestation and Forest Degradation. The article proposes three (03) reduction scenarios, which could be applied by the Republic of Congo, to reduce its emissions related to Deforestation and Forest Degradation, in connection with its NERF. Scenario 1 involves a reduction of 8.3 million teCO2/year. Scenario 2 aims to increase this reduction to 4.2 million teCO2/year and Scenario 3 involves a reduction of 2.8 million teCO2/year. Scenario 2 is perfectly suited to the national circumstances of the Republic of Congo, which has embarked on a sustainable development approach. The national REDD strategy, validated by all stakeholders in July 2016, stipulated that the impact of deforestation and forest degradation be limited on the basis of five (05) strategic axes: (i) strengthening sustainable governance and financing, (ii) sustainable management and development of forest resources, (iii) improvement of agricultural systems, (iv) rationalization of the production and use of wood energy and the promotion of other clean energy sources and (v) the development of a green mining sector. Pays à très forte couverture forestière et à très faible taux de déforestation (High Forest Cover, Low Deforestation « HFLD »), la République du Congo a présenté en 2016, son Niveau des Emissions de Référence pour les Forêts (NERF). Ce NERF, approuvé par la Convention Cadre des Nations-Unies sur les Changements Climatiques (CCNUCC) en Juin 2017, est établi à 35,5 millions teCO2/an. Il est organisé autour de l’estimation des émissions historiques de 2000 à 2012 et des émissions futures de 2015 à 2020, liées à la Déforestation et la Dégradation Forestière. L’article propose trois (03) scénarii de réduction, susceptibles d’être appliqués par la République du Congo, pour réduire ses émissions liées à la Déforestation et la Dégradation Forestière, en lien avec son NERF. Le scénario n°1 porte sur une réduction de 8,3 millions teCO2/an. Le scénario n°2 vise à porter cette réduction à 4,2 millions teCO2/an et le scénario n°3 porte sur une réduction de 2,8 millions teCO2/an. Le scénario 2 est parfaitement adapté aux circonstances nationales de la République du Congo qui s’est engagé dans une approche de développement durable. La stratégie nationale REDD+, validée par l’ensemble des parties prenantes en Juillet 2016, à prescrit de limiter l’impact de la déforestation et de la dégradation forestière en se fondant sur cinq (05) axes stratégiques : (i) le renforcement de la gouvernance et des financements durables, (ii) la gestion durable et la valorisation des ressources forestières, (iii) l’amélioration des systèmes agricoles, (iv) la rationalisation de la production et de l’utilisation du bois énergie et la promotion d'autres sources d'énergie propres et (v) le développement d’un secteur minier vert.

The Impact of Terrorism on Construction Industry in Iraq

2015 ◽  
Vol 3 (2) ◽  
pp. 69-84
Author(s):  
Wadhah Amer Hatem ◽  
Samiaah M. Hassen Al-Tmeemy
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Historical Data ◽  
Terrorist Attacks ◽  
Construction Sector ◽  
Statistical Procedures ◽  
Qualitative Approaches ◽  
Suicide Attacks ◽  
The Face ◽  
The Impact

     Suicide attacks, bombings, explosions became the part of daily life in Iraq. Consequently, the threat of terrorism put the Iraqi construction sector in the face of unique and unusual challenges that not seen on other countries. These challenges can have extensive impact on construction projects. This paper seeks to examine the impact of the terrorist attacks on construction industry and determine the extent to which the impact of terrorism on construction projects in terms of cost, schedule, and quality. This study adapted quantitative and qualitative approaches to collect data using questionnaire survey and interviews, as well as historical data. The study focused on projects that have been the target of terrorist strikes in Diyala governorate. A variety of statistical procedures were employed in data analysis. The results revealed the extent to which terrorist attacks impact construction projects in terms of cost, time, and quality. The results of this study will enhance the awareness of all construction parties to the impact of the terrorist attacks against construction projects. Eventually, this can develop a risk management assessment and assist contractors to properly protect projects and buildings to minimize injuries and fatalities in the event of terrorism.

Chemical Composition and Metal Speciation in Porewaters from the Upper Qu’Appelle River Basin, Saskatchewan

1993 ◽  
Vol 28 (1) ◽  
pp. 83-110 ◽  
Author(s):  
Richard E. Farrell ◽  
Jae E. Yang ◽  
P. Ming Huang ◽  
Wen K. Liaw
Keyword(s):  
Amino Acids ◽  
Trace Metal ◽  
River Basin ◽  
Drainage Basin ◽  
Metal Speciation ◽  
Anthropogenic Activities ◽  
High Concentration ◽  
Metal Concentrations ◽  
Carbonate Equilibria ◽  
The Impact

Abstract Porewater samples from the upper Qu’Appelle River basin in Saskatchewan, Canada, were analyzed to obtain metal, inorganic ligand and amino add profiles. These data were used to compute the aqueous speciation of the metals in each porewater using the computer program GEOCHEM-PC. The porewaters were classified as slightly to moderately saline. Metal concentrations reflected both the geology of the drainage basin and the impact of anthropogenic activities. Whereas K and Na were present almost entirely as the free aquo ions, carbonate equilibria dominated the speciation of Ca. Mg and Mn (the predominant metal ligand species were of the type MCO3 (s). MCO30. and MHCO3+). Trace metal concentrations were generally within the ranges reported for non-polluted freshwater systems. Whereas the speciation of the trace metals Cr(III) and Co(II) was dominated by carbonate equilibria, Hg(II)-, Zn(II)- and Fe(II)-speciation was dominated by hydroxy-metal complexes of the type M(OH)+ and M(OH)2°. The speciation of Fe(III) was dominated by Fe(OH)3 (s). In porewaters with high chloride concentrations (&gt; 2 mM), however, significant amounts of Hg(II) were bound as HgCl20 and HgClOH0. The aqueous speciation of Al was dominated by Al(OH)4− and Al2Si2O4(OH)6 (s). Total concentrations of dissolved free amino acids varied from 15.21 to 25.17 umole L−1. The most important metal scavenging amino acids were histidine (due to high stability constants for the metal-histidine complexes) and tryptophan (due to its relatively high concentration in the porewaters. i.e., 5.96 to 7.73 umole L−1). Secondary concentrations of various trace metal-amino add complexes were computed for all the porewaters, but metal-amino acid complexes dominated the speciation of Cu(II) in all the porewaters and Ni(II) in two of the porewaters.

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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