scholarly journals Global Invasion Risk Assessment of Prosopis juliflora at Biome Level: Does Soil Matter?

Biology ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 203
Author(s):  
Mohammed A. Dakhil ◽  
Ali El-Keblawy ◽  
Mohamed A. El-Sheikh ◽  
Marwa Waseem A. Halmy ◽  
Taoufik Ksiksi ◽  
...  
Keyword(s):  
Driving Forces ◽  
Human Impacts ◽  
Model Performance ◽  
Species Distribution Modelling ◽  
Prosopis Juliflora ◽  
Invasion Risk ◽  
Distribution Modelling ◽  
Global Invasion ◽  
Semi Arid

Prosopis juliflora is one of the most problematic invasive trees in tropical and subtropical regions. Understanding driving forces affecting the potential global distribution would help in managing its current and future spread. The role of climate on the global spatial distribution of P. juliflora has been well studied, but little is known about the role of soil and human impacts as potential drivers. Here, we used maximum entropy (MaxEnt) for species distribution modelling to understand the role of climate (C), soil (S) and human impacts (H), C+S, and C+S+H in controlling the potential invasion range of P. juliflora, and to project its global potential invasive risk. We defined the top threatened global biomes, as predicted by the best-selected model. The incorporation of the edaphic factors improved the model performance and enhanced the accuracy of the outcome. Our findings revealed that the potential invasion risk increases with increases in mean temperature of the driest quarter (Bio9), soil alkalinity and clay fractions. Arid and semi-arid lands are at the highest risk of invasion than other moist biomes.

Plant invasion risk: A quest for invasive species distribution modelling in managing protected areas

2018 ◽  
Vol 95 ◽  
pp. 311-319 ◽  
Author(s):  
Manuele Bazzichetto ◽  
Marco Malavasi ◽  
Vojtěch Bartak ◽  
Alicia Teresa Rosario Acosta ◽  
Duccio Rocchini ◽  
...  
Keyword(s):  
Invasive Species ◽  
Protected Areas ◽  
Species Distribution ◽  
Plant Invasion ◽  
Species Distribution Modelling ◽  
Invasion Risk ◽  
Distribution Modelling

scholarly journals In or Out of the Checklist? DNA Barcoding and Distribution Modelling Unveil a New Species of Crocidura Shrew for Italy

Diversity ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 380
Author(s):  
Emiliano Mori ◽  
Mattia Brambilla ◽  
Fausto Ramazzotti ◽  
Leonardo Ancillotto ◽  
Giuseppe Mazza ◽  
...  
Keyword(s):  
Species Distribution ◽  
Competitive Exclusion ◽  
Species Distribution Modelling ◽  
Skull Morphology ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Italian Regions ◽  
A New Species ◽  
Species Ecology

The genus Crocidura (Eulipotyphla, Soricidae) is the most speciose genus amongst mammals, i.e., it includes the highest number of species. Different species are distinguished by skull morphology, which often prevents the identification of individuals in the field and limits research on these species’ ecology and biology. We combined species distribution models and molecular analyses to assess the distribution of cryptic Crocidura shrews in Italy, confirming the occurrence of the greater white-toothed shrew Crocidura russula in the northwest of the country. The molecular identification ascertained the species’ presence in two distinct Italian regions. Accordingly, species distribution modelling highlighted the occurrence of areas suitable for C. russula in the westernmost part of northern Italy. Our results confirm the role of Italy as a mammal hotspot in the Mediterranean; additionally, they also show the need to include C. russula in Italian faunal checklists. To conclude, we highlight the usefulness of combining different approaches to explore the presence of cryptic species outside their known ranges. Since the similar, smaller C. suaveolens may be displaced by the larger C. russula through competitive exclusion, the latter might be the species actually present where C. suaveolens had been reported previously. A comprehensive and detailed survey is therefore required to assess the current distribution of these species.

scholarly journals The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

2012 ◽  
Vol 88 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Mary Susanne Wisz ◽  
Julien Pottier ◽  
W. Daniel Kissling ◽  
Loïc Pellissier ◽  
Jonathan Lenoir ◽  
...  
Keyword(s):  
Species Distribution ◽  
Biotic Interactions ◽  
Species Distribution Modelling ◽  
Distribution Modelling

scholarly journals Species Distribution Modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin, Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Nurhussen Ahmed ◽  
Clement Atzberger ◽  
Worku Zewdie
Keyword(s):  
Machine Learning ◽  
Invasive Species ◽  
River Basin ◽  
Species Distribution ◽  
Regression Models ◽  
Species Distribution Modelling ◽  
Prosopis Juliflora ◽  
Distribution Modelling ◽  
Awash River Basin ◽  
Sentinel 2

Abstract Background Species Distribution Modelling (SDM) coupled with freely available multispectral imagery from Sentinel-2 (S2) satellite provides an immense contribution in monitoring invasive species. However, attempts to evaluate the performances of SDMs using S2 spectral bands and S2 Radiometric Indices (S2-RIs) and biophysical variables, in particular, were limited. Hence, this study aimed at evaluating the performance of six commonly used SDMs and one ensemble model for S2-based variables in modelling the current distribution of Prosopis juliflora in the lower Awash River basin, Ethiopia. Thirty-five variables were computed from Sentinel-2B level-2A, and out of the variables, twelve significant variables were selected using Variable Inflation Factor (VIF). A total of 680 presence and absence data were collected to train and validate variables using the tenfold bootstrap replication approach in the R software “sdm” package. The performance of the models was evaluated using sensitivity, specificity, True Skill Statistics (TSS), kappa coefficient, area under the curve (AUC), and correlation. Results Our findings demonstrated that except bioclim all machine learning and regression models provided successful prediction. Among the tested models, Random Forest (RF) performed better with 93% TSS and 99% AUC followed by Boosted Regression Trees (BRT), ensemble, Generalized Additive Model (GAM), Support Vector Machine (SVM), and Generalized Linear Model (GLM) in decreasing order. The relative influence of vegetation indices was the highest followed by soil indices, biophysical variables, and water indices in decreasing order. According to RF prediction, 16.14% (1553.5 km2) of the study area was invaded by the alien species. Conclusions Our results highlighted that S2-RIs and biophysical variables combined with machine learning and regression models have a higher capacity to model invasive species distribution. Besides, the use of machine learning algorithms such as RF algorithm is highly essential for remote sensing-based invasive SDM.

Species distribution modelling of the Southern Ocean benthos: a review on methods, cautions and solutions

2021 ◽  
pp. 1-24
Author(s):  
Charlène Guillaumot ◽  
Bruno Danis ◽  
Thomas Saucède
Keyword(s):  
Southern Ocean ◽  
Species Distribution ◽  
Model Performance ◽  
Species Distribution Modelling ◽  
Projection Area ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Influence Model ◽  
Modelling Studies

Abstract Species distribution modelling studies the relationship between species occurrence records and their environmental setting, providing a valuable approach to predicting species distribution in the Southern Ocean (SO), a challenging region to investigate due to its remoteness and extreme weather and sea conditions. The specificity of SO studies, including restricted field access and sampling, the paucity of observations and difficulties in conducting biological experiments, limit the performance of species distribution models. In this review, we discuss some issues that may influence model performance when preparing datasets and calibrating models, namely the selection and quality of environmental descriptors, the spatial and temporal biases that may affect the quality of occurrence data, the choice of modelling algorithms and the spatial scale and limits of the projection area. We stress the importance of evaluating and communicating model uncertainties, and the most common evaluation metrics are reviewed and discussed accordingly. Based on a selection of case studies on SO benthic invertebrates, we highlight important cautions to take and pitfalls to avoid when modelling the distribution of SO species, and we provide some guidelines along with potential methods and original solutions that can be used for improving model performance.

Chronic Pain: Fundamental Scientific Considerations, Specifically for Legal Claims

2013 ◽  
Vol 18 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Robert J. Barth
Keyword(s):  
Health Outcomes ◽  
Pain Perception ◽  
Driving Forces ◽  
Psychological Treatment ◽  
Dominant Role ◽  
Meta Analysis ◽  
General Medicine ◽  
Pain Syndrome ◽  
Problematic Relationship

Abstract Scientific findings have indicated that psychological and social factors are the driving forces behind most chronic benign pain presentations, especially in a claim context, and are relevant to at least three of the AMA Guides publications: AMA Guides to Evaluation of Disease and Injury Causation, AMA Guides to Work Ability and Return to Work, and AMA Guides to the Evaluation of Permanent Impairment. The author reviews and summarizes studies that have identified the dominant role of financial, psychological, and other non–general medicine factors in patients who report low back pain. For example, one meta-analysis found that compensation results in an increase in pain perception and a reduction in the ability to benefit from medical and psychological treatment. Other studies have found a correlation between the level of compensation and health outcomes (greater compensation is associated with worse outcomes), and legal systems that discourage compensation for pain produce better health outcomes. One study found that, among persons with carpal tunnel syndrome, claimants had worse outcomes than nonclaimants despite receiving more treatment; another examined the problematic relationship between complex regional pain syndrome (CRPS) and compensation and found that cases of CRPS are dominated by legal claims, a disparity that highlights the dominant role of compensation. Workers’ compensation claimants are almost never evaluated for personality disorders or mental illness. The article concludes with recommendations that evaluators can consider in individual cases.

Convergence of Corporate Governance Models

2004 ◽  
pp. 129-140 ◽  
Author(s):  
M. Tretyakov
Keyword(s):  
Corporate Governance ◽  
Institutional Environment ◽  
Driving Forces ◽  
Commodity Markets ◽  
Legal Systems ◽  
National Institutions ◽  
Governance Models ◽  
Changing Role

The article focuses on the analysis of the process of convergence of outsider and insider models of corporate governance. Chief characteristics of basic and intermediate systems of corporate governance as well as the changing role of its main agents are under examination. Globalization of financial and commodity markets, convergence of legal systems, an open exchange of ideas and information are the driving forces of the convergence of basic systems of corporate governance. However the convergence does not imply the unification of institutional environment and national institutions of corporate governance.

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