Modelling the partially unknown distribution of wall lizards (Podarcis) in North Africa: ecological affinities, potential areas of occurrence, and methodological constraints

2008 ◽  
Vol 86 (9) ◽  
pp. 992-1001 ◽  
Author(s):  
A. Kaliontzopoulou ◽  
J. C. Brito ◽  
M. A. Carretero ◽  
S. Larbes ◽  
D. J. Harris
Keyword(s):  
North Africa ◽  
Habitat Type ◽  
Model Performance ◽  
Species Distribution Modelling ◽  
Data Sets ◽  
Mountain Ranges ◽  
Presence Data ◽  
Scale Models ◽  
Two Factors ◽  
Negative Effect

Species distribution modelling (SDM) is a powerful tool to investigate various biological questions with a spatial component, but is also sensitive to presence-data characteristics, particularly data precision and clustering. Here, we investigate the effect of these two factors on SDM using Maxent as the modelling technique and wall lizards (genus Podarcis Wagler, 1830) from North Africa as a model system. Podarcis are not ubiquitous in Africa as they are in Europe, but their ecological and distributional characteristics in this area are poorly known. Our results show that the most important environmental factors related to the distribution of this genus in North Africa are humidity, habitat type, and temperature. The areas of potential distribution predicted by models based on data sets with different precision and clustering characteristics show high relatedness to coastal areas and mountain ranges and extend to areas were presence records for these lizards are lacking. Our comparison of models based on different data sets indicates that finer scale models, even if based on fewer presence locations, outperform coarser scale ones. Data clustering does not have a negative effect on model performance, but is rather overcome by sample-size effects. Similar approaches may be of general application to other stenoic species for which available locations are scarce in comparison with the extension of the study area.

Chasing the phantom: biogeography and conservation of Vipera latastei-monticola in the Maghreb (North Africa)

2018 ◽  
Vol 39 (2) ◽  
pp. 145-161 ◽  
Author(s):  
Inês Freitas ◽  
Soumia Fahd ◽  
Guillermo Velo-Antón ◽  
Fernando Martínez-Freiría
Keyword(s):  
North Africa ◽  
Habitat Degradation ◽  
Conservation Status ◽  
Western Mediterranean ◽  
Niche Modelling ◽  
Habitat Transformation ◽  
Mountain Ranges ◽  
Management Actions ◽  
Suitable Space ◽  
The Impact

Abstract The Maghreb region (North Africa) constitutes a major component of the Mediterranean Basin biodiversity hotspot. During the last centuries, a consistent human population growth has led to an unprecedented rate of habitat transformation and loss in the region and thus, threatening its biodiversity. The Western Mediterranean viper Vipera latastei-monticola inhabits humid and subhumid areas in the main mountain ranges of the Maghreb, facing such threatening factors; however, its elusive character and rarity hindered data collection for distinct biological purposes. Here, we study the biogeographical patterns and conservation status of the Maghrebian V. latastei-monticola resulting from recent sampling campaigns in Morocco and Tunisia. We update species distribution, and integrate phylogeographic and ecological niche modelling analyses at both species and lineage level to identify suitable areas, and to evaluate the impact of anthropogenic transformation and level of protection of their suitable space. We identified four highly divergent mitochondrial lineages, including a new lineage endemic to the Western High Atlas, with allopatric distributions and restricted to mountain ranges, supporting the role of mountains as past climatic refugia. Despite the remoteness of suitable areas, we report widespread habitat degradation and identify the low effectiveness of the current protected areas system in preserving the species and lineages range. Our study shows the urgent need to apply management actions for the long-term conservation of this vulnerable species and suggests a revaluation of the specific status of V. monticola, as these populations likely represent an ecotype of V. latastei.

scholarly journals Influence of the Upstream Terrain on the Formation of a Cold Frontal Snowband in Northeast China

2021 ◽  
Author(s):  
Na Li ◽  
Baofeng Jiao ◽  
Lingkun Ran ◽  
Zongting Gao ◽  
Shouting Gao
Keyword(s):  
Gravity Waves ◽  
Northeast China ◽  
Large Scale ◽  
Control Experiment ◽  
Vertical Motion ◽  
Near Surface ◽  
Inertial Instability ◽  
Two Factors ◽  
Negative Effect ◽  
Conditional Instability

AbstractWe investigated the influence of upstream terrain on the formation of a cold frontal snowband in Northeast China. We conducted numerical sensitivity experiments that gradually removed the upstream terrain and compared the results with a control experiment. Our results indicate a clear negative effect of upstream terrain on the formation of snowbands, especially over large-scale terrain. By thoroughly examining the ingredients necessary for snowfall (instability, lifting and moisture), we found that the release of mid-level conditional instability, followed by the release of low-level or near surface instabilities (inertial instability, conditional instability or conditional symmetrical instability), contributed to formation of the snowband in both experiments. The lifting required for the release of these instabilities was mainly a result of frontogenetic forcing and upper gravity waves. However, the snowband in the control experiment developed later and was weaker than that in the experiment without upstream terrain. Two factors contributed to this negative topographic effect: (1) the mountain gravity waves over the upstream terrain, which perturbed the frontogenetic circulation by rapidly changing the vertical motion and therefore did not favor the release of instabilities in the absence of persistent ascending motion; and (2) the decrease in the supply of moisture as a result of blocking of the upstream terrain, which changed both the moisture and instability structures leeward of the mountains. A conceptual model is presented that shows the effects of the instabilities and lifting on the development of cold frontal snowbands in downstream mountains.

scholarly journals An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level

2020 ◽  
Vol 12 (1) ◽  
pp. 580-597
Author(s):  
Mohamad Hamzeh ◽  
Farid Karimipour
Keyword(s):  
Spatial Data ◽  
Spatial Models ◽  
Model Performance ◽  
Essential Elements ◽  
Petroleum System ◽  
Petroleum Exploration ◽  
System Level ◽  
Data Sets ◽  
Petroleum Potential ◽  
Spatial Data Sets

AbstractAn inevitable aspect of modern petroleum exploration is the simultaneous consideration of large, complex, and disparate spatial data sets. In this context, the present article proposes the optimized fuzzy ELECTRE (OFE) approach based on combining the artificial bee colony (ABC) optimization algorithm, fuzzy logic, and an outranking method to assess petroleum potential at the petroleum system level in a spatial framework using experts’ knowledge and the information available in the discovered petroleum accumulations simultaneously. It uses the characteristics of the essential elements of a petroleum system as key criteria. To demonstrate the approach, a case study was conducted on the Red River petroleum system of the Williston Basin. Having completed the assorted preprocessing steps, eight spatial data sets associated with the criteria were integrated using the OFE to produce a map that makes it possible to delineate the areas with the highest petroleum potential and the lowest risk for further exploratory investigations. The success and prediction rate curves were used to measure the performance of the model. Both success and prediction accuracies lie in the range of 80–90%, indicating an excellent model performance. Considering the five-class petroleum potential, the proposed approach outperforms the spatial models used in the previous studies. In addition, comparing the results of the FE and OFE indicated that the optimization of the weights by the ABC algorithm has improved accuracy by approximately 15%, namely, a relatively higher success rate and lower risk in petroleum exploration.

Does digitalization create or reduce perceived global value?

2018 ◽  
Vol 35 (7) ◽  
pp. 676-687 ◽  
Author(s):  
Ibtissame Abaidi ◽  
Eric Vernette
Keyword(s):  
Undergraduate Students ◽  
Large Scale ◽  
Costs And Benefits ◽  
Content Type ◽  
Complex Effect ◽  
Digital Format ◽  
Two Factors ◽  
Negative Effect ◽  
Cost And Benefit Analysis ◽  
Print Format

PurposeThe internet has made it possible to diffuse totally digitized products on a very large scale. The newspaper business is one of the sectors that has been most affected by this technological revolution. Given such products’ uneven commercial success, an analysis of the literature suggests that these mixed results could be explained by the digitized nature of the product combined with a price judged too high. Both these elements reduce the perceived global value of the digital support compared with the print version on paper. To test this proposition, the authors have constructed an experimental design, manipulating the format (digital newspaper vs. print newspaper) and the price (high vs low). The results show that newspaper digitization significantly reduces perceived global value for the consumer compared with the print format. The authors also show that the perceived intangibility of the product exerts a more complex effect on perceived global value: this effect depends on both the nature of the intangibility (mental vs physical) and the cost and benefit analysis.Design/methodology/approachAn experimental study was conducted with two factors: digitalization (print vs digital format) and price (low vs high). The authors carried out a mixed-factor variance analysis and follow Preacher and Hayes procedure to test the hypothesis. A sample of 387 undergraduate students was interviewed in laboratory.FindingsThe results show that newspaper digitization significantly reduces (i.e. destroys) perceived global value for the consumer (i.e. it destroys value), compared to the print format. The reuslts also show that the perceived intangibility of the product exerts a more complex effect on perceived global value: this effect depends at the same time on the nature of the intangibility (mental vs physical) and the account taken of costs and benefits.Originality/valueOne major result is the fact that digitizing newspaper strongly destroys its perceived global value for the consumer, compared to the physical alternative. To explain this phenomenon, the product’s perceived intangibility had been considered, as well as how this is related to the perceived costs and benefits. It appears that it has an overall direct negative effect on perceived value; therefore, the more a newspaper format is perceived as physically intangible, the more its perceived global value decreases. Results shows that this loss of value can be counteracted in two different ways, through the indirect effects of costs and benefits.

Chinese perception and willingness to buy Taiwanese brands

2018 ◽  
Vol 30 (4) ◽  
pp. 816-836 ◽  
Author(s):  
Nizar Souiden ◽  
Riadh Ladhari ◽  
Liu Chang
Keyword(s):  
Structural Equation ◽  
Equation Modeling ◽  
Strong Ties ◽  
Content Type ◽  
Foreign Companies ◽  
Brand Quality ◽  
Willingness To Buy ◽  
Two Factors ◽  
Negative Effect ◽  
The Impact

Purpose The purpose of this paper is to examine ethnocentrism and animosity in a special context of two societies that share cultural, historical, ethnic and geographical characteristics. In particular, it first investigates the relationships between Chinese ethnocentrism and animosity toward Taiwan, and then it examines the impact of these two factors on the Chinese perception of Taiwanese brand quality and their purchase intent. Design/methodology/approach Based on a sample of 605 respondents from China, data were analyzed by structural equation modeling. Findings The results show that although Chinese animosity toward Taiwan is moderate, it is significantly driven by ethnocentrism, which has a significant and negative effect on willingness to buy, but not on the perception of Taiwanese brand quality. The Chinese animosity toward Taiwan, however, has negative and significant effects on their perception of Taiwanese brand quality and their intention of purchasing Taiwanese brands. Research limitations/implications The immense size of the country has impeded the representativeness of the authors’ sample and the generalizability of the results. Also, the study covers only one type of product. Practical implications Forming partnerships with local Chinese businesses and developing strong ties with local communities could be considered as a solution to minimize or circumvent the effect of animosity and might help foreign companies appear more “local.” Originality/value In contrast to past studies that investigated ethnocentrism and animosity in the context of countries presenting several differences (e.g. China vs USA), this study investigates the effect of ethnocentrism and animosity in the context of two countries (China and Taiwan) that share cultural, historical, ethnic and geographic characteristics. Despite the strong ties between the two countries, the Chinese have a certain animosity, though moderate, toward Taiwan and consequently are less inclined to buy Taiwanese brands. This implies that Chinese animosity toward a country may be toned down or pronounced, depending on whether they have strong or weak ties with that country.

scholarly journals Success’ Conditions of Microfinance to Fostering Sustainable Development

2020 ◽  
Vol 13 (1) ◽  
pp. 22
Author(s):  
Mongi Lassoued
Keyword(s):  
Sustainable Development ◽  
North Africa ◽  
Empirical Studies ◽  
World Bank Group ◽  
Mena Region ◽  
Loan Portfolio ◽  
Mena Countries ◽  
Negative Effect ◽  
Bank Group ◽  
The Impact

With a loan portfolio estimated at $124.1 billion in 2018, 139.9 million borrowers benefited from microfinance services, compared to just 98 million in 2009 (World Bank Group, 2018). Despite a low quality portfolio and high borrowers' costs, the portfolio in the Middle East and North Africa (MENA) shows a remarkable increase of 20% but with a decrease of 6.6 points (Microfinance Barometer, 2019). Most of empirical studies have focused on the issue of microfinance, and research conducted on the effectiveness of microcredit is surprisingly scarce or even non-existent in the MENA region. In addition, microcredit could lead to sustainable development in the region via an income effect. The main objective of this paper is to determine the impact of microcredit on sustainable development for 10 selected MENA countries over the period 1990-2018. Empirical results paradoxically show a negative effect of microcredit on sustainable development. Although, the limitations of data, the present paper also contributes to the existing literature by advising conditions for the success of microcredit aiming for a better promotion of sustainable development.

Coming Out, Entertainment Television, and the Youth Revolt

2018 ◽  
pp. 148-177
Author(s):  
Jeremiah J. Garretson
Keyword(s):  
Public Opinion ◽  
Attitude Change ◽  
Coming Out ◽  
Millennial Generation ◽  
Direct Contact ◽  
Data Sets ◽  
Distinctive Features ◽  
Two Factors ◽  
Entertainment Television ◽  
Rights Issues

This chapter begins by describing the dramatic increase in direct contact of the American public with LGBTQ people documented using polling data. Trends in depictions of LGBTQ people on television and film are outlined, which mirror the expansion of direct contact with LGBTQs. These two factors---direct contact and meditated contact---are processed in similar ways psychologically according to affective liberalization. Both are predicted to be more effective at attitude change among younger people. The theory is then empirically tested using four different expansive cross-time public opinion datasets. All four analyses of the data-sets come to same conclusion, contact with LGBTQs (mediated and interpersonal) explains all the distinctive features of attitude change---its large magnitude, its timing, its broadness across specific gay rights issues, and its concentration among the millennial generation.

scholarly journals Kernel Joint Sparse Representation Based on Self-Paced Learning for Hyperspectral Image Classification

2019 ◽  
Vol 11 (9) ◽  
pp. 1114
Author(s):  
Sixiu Hu ◽  
Jiangtao Peng ◽  
Yingxiong Fu ◽  
Luoqing Li
Keyword(s):  
Sparse Representation ◽  
Hyperspectral Image ◽  
Feature Space ◽  
Classification Performance ◽  
Hyperspectral Data ◽  
Data Sets ◽  
Neighborhood Structure ◽  
Joint Sparse Representation ◽  
Negative Effect ◽  
Sparse Coefficient

By means of joint sparse representation (JSR) and kernel representation, kernel joint sparse representation (KJSR) models can effectively model the intrinsic nonlinear relations of hyperspectral data and better exploit spatial neighborhood structure to improve the classification performance of hyperspectral images. However, due to the presence of noisy or inhomogeneous pixels around the central testing pixel in the spatial domain, the performance of KJSR is greatly affected. Motivated by the idea of self-paced learning (SPL), this paper proposes a self-paced KJSR (SPKJSR) model to adaptively learn weights and sparse coefficient vectors for different neighboring pixels in the kernel-based feature space. SPL strateges can learn a weight to indicate the difficulty of feature pixels within a spatial neighborhood. By assigning small weights for unimportant or complex pixels, the negative effect of inhomogeneous or noisy neighboring pixels can be suppressed. Hence, SPKJSR is usually much more robust. Experimental results on Indian Pines and Salinas hyperspectral data sets demonstrate that SPKJSR is much more effective than traditional JSR and KJSR models.

Introduction to Fuzzy Data Mining Methods

2011 ◽  
pp. 55-95 ◽  
Author(s):  
Balazs Feil ◽  
Janos Abonyi
Keyword(s):  
Data Mining ◽  
Model Performance ◽  
Fuzzy Rule ◽  
Classification Problem ◽  
Data Sets ◽  
Rule Based ◽  
Data Mining Algorithms ◽  
Rule Bases ◽  
Mining Algorithms ◽  
Extraction Model

This chapter aims to give a comprehensive view about the links between fuzzy logic and data mining. It will be shown that knowledge extracted from simple data sets or huge databases can be represented by fuzzy rule-based expert systems. It is highlighted that both model performance and interpretability of the mined fuzzy models are of major importance, and effort is required to keep the resulting rule bases small and comprehensible. Therefore, in the previous years, soft computing based data mining algorithms have been developed for feature selection, feature extraction, model optimization, and model reduction (rule based simplification). Application of these techniques is illustrated using the wine data classification problem. The results illustrate that fuzzy tools can be applied in a synergistic manner through the nine steps of knowledge discovery.

scholarly journals Surface-Related Features Responsible for Cytotoxic Behavior of MXenes Layered Materials Predicted with Machine Learning Approach

Materials ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3083
Author(s):  
Maciej E. Marchwiany ◽  
Magdalena Birowska ◽  
Mariusz Popielski ◽  
Jacek A. Majewski ◽  
Agnieszka M. Jastrzębska
Keyword(s):  
Machine Learning ◽  
Transition Metal Oxides ◽  
2D Materials ◽  
Experimental Studies ◽  
Biological Data ◽  
Data Sets ◽  
Toxicological Studies ◽  
Two Factors ◽  
Health Need

To speed up the implementation of the two-dimensional materials in the development of potential biomedical applications, the toxicological aspects toward human health need to be addressed. Due to time-consuming and expensive analysis, only part of the continuously expanding family of 2D materials can be tested in vitro. The machine learning methods can be used—by extracting new insights from available biological data sets, and provide further guidance for experimental studies. This study identifies the most relevant highly surface-specific features that might be responsible for cytotoxic behavior of 2D materials, especially MXenes. In particular, two factors, namely, the presence of transition metal oxides and lithium atoms on the surface, are identified as cytotoxicity-generating features. The developed machine learning model succeeds in predicting toxicity for other 2D MXenes, previously not tested in vitro, and hence, is able to complement the existing knowledge coming from in vitro studies. Thus, we claim that it might be one of the solutions for reducing the number of toxicological studies needed, and allows for minimizing failures in future biological applications.

Sign in / Sign up

Export Citation Format

Share Document