scholarly journals Distribution of Cranberry Blue Butterflies (Agriades optilete) and Their Responses to Forest Disturbance from In Situ Oil Sands and Wildfires

Diversity ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Federico Riva ◽  
John Acorn ◽  
Scott Nielsen
Keyword(s):  
Boreal Forests ◽  
Oil Sands ◽  
Species Distribution Model ◽  
Forest Disturbance ◽  
Probability Of Detection ◽  
Distribution Model ◽  
Habitat Specificity ◽  
Northern Alberta ◽  
Seismic Lines

Cranberry blues (Agriades optilete) are butterflies of conservation interest worldwide. Less than 20 populations are known in Alberta, Canada, mostly inhabiting boreal forests that are increasingly fragmented by oil sands developments and subject to wildfires. We modeled the abundance of cranberry blues in the boreal forests of Alberta’s Wood Buffalo Region as a function of forest characteristics, presence of disturbances associated with in situ oil sands exploration, and wildfire disturbance, while accounting for butterfly detectability as a function of sampling conditions. We counted 188 cranberry blues during 1280 samples, discovering 14 unknown populations using a species distribution model based on forest wetness and canopy height. Probability of detection peaked around 5th July, and at higher temperatures and in the absence of wind, with cranberry blues preferring wetter treed peatland forests with low canopy heights. Seismic lines were positively related to the abundance of cranberry blues (400% increase), while exploratory well pads and wildfires were negatively related (60% and 90% loss, respectively). Overall, cranberry blue populations are small and locally sensitive to both natural and anthropogenic disturbances. Despite a narrow habitat specificity, cranberry blues seem more widely distributed than previously thought in northern Alberta (57% of the study area deemed suitable).

scholarly journals Tar on Tap

2008 ◽  
Vol 130 (12) ◽  
pp. 30-34
Author(s):  
Bridget Mintz Testa
Keyword(s):  
Oil Sands ◽  
Surface Mining ◽  
Recycled Water ◽  
Petroleum Production ◽  
Production Processes ◽  
Production Wells ◽  
Oil Demand ◽  
Northern Alberta ◽  
In Situ Production

This article explores diverse ways adopted by companies to find ways to make extracting oil from the sands of northern Alberta a little easier. At Petrobank’s Whitesands site, heat from in situ combustion both melts and upgrades the bitumen in the underground deposit. Horizontal production wells carry the oil to the surface. However, even with the new processes in place, copious quantities of energy and water are needed to produce oil from sands. In situ production processes exploit bitumen deposits that are inaccessible through surface mining. The facility at EnCana’s Foster Creek site processes some of the water used to extract bitumen in situ. That recycled water is then boiled and reinjected below the surface. Environmental arguments aside, many observers contend that the only argument against exploiting the Alberta oil sands that might have any success is economic—that it might cost more than alternatives. The paper concludes that barring some unforeseen calamity, oil demand is expected to outstrip the capacity of conventional petroleum production. Even if wringing oil from the Alberta sands is expensive and energy-intensive, it is probably a cost most consumers will be willing to pay for access to the next easiest oil.

scholarly journals Narrow anthropogenic corridors direct the movement of a generalist boreal butterfly

2018 ◽  
Vol 14 (2) ◽  
pp. 20170770 ◽  
Author(s):  
Federico Riva ◽  
John H. Acorn ◽  
Scott E. Nielsen
Keyword(s):  
Species Interactions ◽  
Boreal Forests ◽  
Oil Sands ◽  
The Arctic ◽  
Initial Direction ◽  
Seismic Line ◽  
Habitat Generalist ◽  
Seismic Lines ◽  
Vast Area ◽  
Petroleum Oil

Ecological and anthropogenic corridors are becoming more common worldwide, but little is known about how corridor size (width) affects species' movements, and thus their effects. Here we investigated whether 4- and 8-m wide anthropogenic corridors (seismic lines) cleared for petroleum (oil sands) exploration in boreal forests in Alberta, Canada, act on altering the behaviour of a habitat generalist butterfly, the Arctic fritillary ( Boloria chariclea ). Specifically, we captured 539 Arctic fritillaries and released them in seismic line corridor or control sites with no structural directionality (i.e. forests and clearings), and recorded both their initial direction (along the seismic line or not) and persistence in directional movements. Arctic fritillaries moved inside these lines twice as often as they left them, and maintained their initial direction more often, regardless of line size and independently of forest structure or sex of individuals. Thus, anthropogenic corridors as narrow as 4 m can affect insect movements. Given the vast area of boreal forests disturbed from seismic assessments, investigating if the effects of these dense, localized lines affect population dynamics and species interactions would provide important insights to managing this ecosystem and identifying restoration actions.

scholarly journals Assess the Extinction Risk of Mountain Endemic Plants in Egypt Under the Current Climatic Condition: A Case Study of Endemic Silene Species

2021 ◽  
Vol 2 (5) ◽  
pp. 34-47
Author(s):  
Karim Omar ◽  
Ibrahim Elgamal
Keyword(s):  
Species Distribution Model ◽  
Extinction Risk ◽  
Field Research ◽  
Iucn Red List ◽  
Red List ◽  
Ex Situ ◽  
Distribution Model ◽  
High Mountain ◽  
Endemic Plant

The process of developing a conservation programme for endemic plant species, in particular those with a small geographical size in mountain ecosystems, whether in situ of ex situ, is a very complex matter, especially if data on the state of the environment and conservation are unavailable. Silene leucophylla and Silene oreosinaica are perennial plants endemic to St. Catherine Protected Area (SCPA), which locate at South Sinai, Egypt. For long time, the second species has not been observed in the field. As a result, the purpose of this study was to increase understanding of the two species' ecological and conservation statuses by: The first step is to confirm their existence on the ground; the second step is to determine the present ecological and conservation conditions through an extinction risk assessment by using IUCN Red List methodology; and the third step is the use of Species Distribution Model (SDM) to locate and extract current appropriate habitat suitability. The field research, which was conducted between March to December 2017, resulted in building knowledge of the current distribution, characteristics of current species populations, and status of ecology and habitat, in addition to identifying the main threats. Both species have been recorded in 20 major sites, in a very restricted area, particularly in a high mountain region (19 sites of Silene leucophylla and 3 sites of S. oreosinaica), with Extent of Occurrence about 468.2 km2 for Silene leucophylla and 24.5 km2 for S. oreosinaica. The population size was very small and fragmented and the extreme drought and overgrazing clearly affected both species. Based on the collected data, the extinction risk was calculated as Critically Endangered for S. oreosinaica and as Endangered for S. leucophylla according to IUCN Red List. For both species, appropriate habitat is concentrated in the high mountain ranges in the central north section of the SCPA, according to SDM. For Silene leucophylla, a presence probability of 20.5 km2 was anticipated, whereas for S. oreosinaica, a presence probability of 62.1 km2 had been predicted. Conservation methods are advocated both in situ (via recovery) and ex situ (by seed collecting and storage, awareness building, and grazing control).

Oil and Water Content Measurements in Bitumen Ore and Froth Samples Using Low Field NMR

2006 ◽  
Vol 9 (06) ◽  
pp. 654-663 ◽  
Author(s):  
Jonathan L. Bryan ◽  
An T. Mai ◽  
Florence M. Hum ◽  
Apostolos Kantzas
Keyword(s):  
Water Content ◽  
Oil Sands ◽  
Oil Sand ◽  
Low Field ◽  
Oil Sands Mining ◽  
Characterization Studies ◽  
Oil Water ◽  
Solids Content ◽  
Northern Alberta

Summary Low-field nuclear magnetic resonance (NMR) relaxometry has been used successfully to perform estimates of oil and water content in unconsolidated oil-sand samples. This work has intriguing applications in the oil-sands mining and processing industry, in the areas of ore and froth characterization. Studies have been performed on a database of ore and froth samples from the Athabasca region in northern Alberta, Canada. In this paper, new automated algorithms are presented that predict the oil- and water-weight content of oil-sand ores and froths. Suites of real and synthetic samples of bitumen, water, clay, and sand have also been used to investigate the physical interactions of the different parameters on the NMR spectra. Preliminary observations regarding spectral properties indicate that it may be possible in the future to estimate the amount of clay in the samples, based upon shifts in the NMR spectra. NMR estimates of oil and water content are fairly accurate, thus enhancing the possibility of using NMR for oil-sands development and in the oil-sands mining industry. Introduction The oil sands of northern Alberta contain some of the world's largest deposits of heavy oil and bitumen. As our conventional oil reserves continue to decline, these oil sands will be the future of the Canadian oil industry for years to come and will allow Canada to continue to be a world leader in both oil production and technology development. Approximately 19% of these bitumen reserves are found in unconsolidated deposits that lie close enough to the surface that they can be recovered with surface-mining technology (Alberta Energy and Utilities Board 2004). In 2003, this translated to 35% of all heavy-oil and bitumen production (Alberta Energy and Utilities Board 2004), and numerous companies have invested billions of dollars in oil-sands mine-development projects. Furthermore, many in-situ bitumen-recovery options are currently being designed and field tested for recovering oil in deeper formations (Natl. Energy Board 2004). Being able to predict oil properties and fluid saturation in situ and process optimization of bitumen extraction (frothing) is therefore of considerable value to the industry. There are several areas in oil-sands development operations where it is important to have an estimate of the oil, water, and solids content of a given sample. During initial characterization of the reservoir, it is necessary to determine oil and water content with depth and location in the reservoir. Fluid-content determination with logging tools would be beneficial for all reservoir-characterization studies, whether for oil-sands mining or in-situ bitumen recovery. In mining operations, during the processing of the mined oil-sand ore, having information about the oil, water, and solids content during the extraction process will allow for improved process optimization and control. The industry standard for measuring oil, water, and solids content accurately is the Dean-Stark (DS) extraction method (Core Laboratories 1992). This is essentially a distillation procedure, whereby boiling solvent is used to vaporize water and separate the oil from the sand. Oil, water, and solids are separated and their contents measured separately. The problem with DS is that it requires large amounts of solvents and is time consuming. Centrifuge technology is often used for faster process control, but this can be inaccurate because of similar fluid densities and the presence of emulsions. New methods for fast measurements of oil, water, and solids content are needed.

scholarly journals A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

2021 ◽  
Vol 13 (8) ◽  
pp. 1495
Author(s):  
Jehyeok Rew ◽  
Yongjang Cho ◽  
Eenjun Hwang
Keyword(s):  
Neural Networks ◽  
Species Distribution ◽  
Best Practice ◽  
Deep Neural Networks ◽  
Species Distribution Models ◽  
Species Distribution Model ◽  
Environmental Data ◽  
Distribution Model ◽  
Distribution Models ◽  
Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

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