scholarly journals Expansion of "Himantoglossum robertianum" (Orchidaceae) in Madrid: a case study on environmental variables and geographical distribution

2018 ◽  
Vol 39 (2) ◽  
Author(s):  
Ignacio Ramos Gutiérrez ◽  
Juan Manuel Martínez Labarga ◽  
José Araújo Díaz ◽  
Alejandro G. Fernández de Castro ◽  
Juan Carlos Moreno Saiz
Keyword(s):  
Geographical Distribution ◽  
Environmental Variables

Assessment and Treatment of Selective Mutism in a Child With Autism Spectrum Disorder

2020 ◽  
pp. 153465012098345
Author(s):  
Mirela Cengher ◽  
Joy C. Clayborne ◽  
Adrianna E. Crouch ◽  
Julia T. O’Connor
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Interaction ◽  
Environmental Variables ◽  
Behavioral Interventions ◽  
Selective Mutism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Future Research ◽  
Assessment And Treatment

Over 60% of children diagnosed with selective mutism are also diagnosed with Autism Spectrum Disorder. Previous research established that behavioral interventions are effective at increasing speech in children with both diagnoses. However, few studies conducted assessments to determine environmental variables that inhibit speech, and such assessments are necessary for the development of effective and efficient treatments. This case study describes an assessment that evaluated the function(s) of selective mutism. The results confirmed that the participant did not talk to avoid social interaction and that mutism occurred primarily in the presence of multiple, unfamiliar people. Our first treatment focused on increasing tolerance for social interaction, demonstrated by an increase in speech production in the presence of unfamiliar people. Our second treatment focused on increasing qualitative aspects of the participant’s speech (i.e., both responses and initiations). Finally, we taught the participant’s parents to implement the treatment in naturalistic settings, and the participant demonstrated generalization of treatment effects across people and settings. Implications for clinical practice and future research are discussed.

Integral projection models

2021 ◽  
pp. 181-196
Author(s):  
Edgar J. González ◽  
Dylan Z. Childs ◽  
Pedro F. Quintana-Ascencio ◽  
Roberto Salguero-Gómez
Keyword(s):  
Population Dynamics ◽  
Environmental Variables ◽  
Linear Models ◽  
Vital Rates ◽  
Matrix Population Models ◽  
Generalised Linear Models ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Over Time

Integral projection models (IPMs) allow projecting the behaviour of a population over time using information on the vital processes of individuals, their state, and that of the environment they inhabit. As with matrix population models (MPMs), time is treated as a discrete variable, but in IPMs, state and environmental variables are continuous and are related to the vital rates via generalised linear models. Vital rates in turn integrate into the population dynamics in a mechanistic way. This chapter provides a brief description of the logic behind IPMs and their construction, and, because they share many of the analyses developed for MPMs, it only emphasises how perturbation analyses can be performed with respect to different model elements. The chapter exemplifies the construction of a simple and a more complex IPM structure with an animal and a plant case study, respectively. Finally, inverse modelling in IPMs is presented, a method that allows population projection when some vital rates are not observed.

Experimental investigation and modeling of photovoltaic soiling loss as a function of environmental variables: A case study of semi-arid climate

2021 ◽  
Vol 221 ◽  
pp. 110874
Author(s):  
Houssain Zitouni ◽  
Alae Azouzoute ◽  
Charaf Hajjaj ◽  
Massaab El Ydrissi ◽  
Mohammed Regragui ◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Environmental Variables ◽  
Arid Climate ◽  
Semi Arid

Habitat type richness associations with environmental variables: a case study in the Greek Natura 2000 aquatic ecosystems

2011 ◽  
Vol 20 (5) ◽  
pp. 929-943 ◽  
Author(s):  
Evangelia G. Drakou ◽  
Athanasios S. Kallimanis ◽  
Antonios D. Mazaris ◽  
Evangelia Apostolopoulou ◽  
John D. Pantis
Keyword(s):  
Aquatic Ecosystems ◽  
Environmental Variables ◽  
Habitat Type ◽  
Natura 2000

scholarly journals Environmental Analysis of GOES-R Proving Ground Convection-Initiation Forecasting Algorithms

2015 ◽  
Vol 54 (7) ◽  
pp. 1637-1662 ◽  
Author(s):  
Jason M. Apke ◽  
Daniel Nietfeld ◽  
Mark R. Anderson
Keyword(s):  
Environmental Variables ◽  
Environmental Influences ◽  
Principal Component ◽  
University Of Alabama ◽  
Algorithm Performance ◽  
University Of Wisconsin ◽  
Improve Algorithm ◽  
Convection Initiation ◽  
The University

AbstractEnhanced temporal and spatial resolution of the Geostationary Operational Environmental Satellite–R Series (GOES-R) will allow for the use of cloud-top-cooling-based convection-initiation (CI) forecasting algorithms. Two such algorithms have been created on the current generation of GOES: the University of Wisconsin cloud-top-cooling algorithm (UWCTC) and the University of Alabama in Huntsville’s satellite convection analysis and tracking algorithm (SATCAST). Preliminary analyses of algorithm products have led to speculation over preconvective environmental influences on algorithm performance. An objective validation approach is developed to separate algorithm products into positive and false indications. Seventeen preconvective environmental variables are examined for the positive and false indications to improve algorithm output. The total dataset consists of two time periods in the late convective season of 2012 and the early convective season of 2013. Data are examined for environmental relationships using principal component analysis (PCA) and quadratic discriminant analysis (QDA). Data fusion by QDA is tested for SATCAST and UWCTC on five separate case-study days to determine whether application of environmental variables improves satellite-based CI forecasting. PCA and significance testing revealed that positive indications favored environments with greater vertically integrated instability (CAPE), less stability (CIN), and more low-level convergence. QDA improved both algorithms on all five case studies using significantly different variables. This study provides an examination of environmental influences on the performance of GOES-R Proving Ground CI forecasting algorithms and shows that integration of QDA in the cloud-top-cooling-based algorithms using environmental variables will ultimately generate a more skillful product.

The relationship among environmental variables, jellyfish and non-gelatinous zooplankton: A case study in the north of the Gulf of Oman

2017 ◽  
Vol 38 (6) ◽  
pp. e12476
Author(s):  
Fatemeh Pourjomeh ◽  
Mohammad Reza Shokri ◽  
Hamid Rezai ◽  
Hassan Rajabi-Maham ◽  
Elham Maghsoudlou
Keyword(s):  
Environmental Variables ◽  
Gelatinous Zooplankton ◽  
Gulf Of Oman ◽  
The North ◽  
The Relationship

scholarly journals Predicting the Potential Distribution of Endangered and Rare Satyrium Species in China under Climate Change

2021 ◽  
Author(s):  
Xianheng Ouyang ◽  
Shihao Bai ◽  
Anliang Chen ◽  
Garry Brien Strachan ◽  
Luying Zuo ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Geographical Distribution ◽  
Environmental Variables ◽  
Environmental Changes ◽  
Characteristic Curve ◽  
Climatic Conditions ◽  
Suitable Habitat ◽  
Management Approaches ◽  
Lower Temperature ◽  
Temperature Seasonality

Satyrium is an endangered and rare genus of plant that has various pharmacodynamic functions. The prediction of potentially suitable habitat of Satyrium species and to analyze their changes, the model MaxEnt niche was applied; furthermore, the receiver operating characteristic curve was applied to analyze accuracy. The results provided an available reference for implementation of long-term conservation and management approaches for the species. Under the current climatic conditions, the area of the total suitable habitat for Satyrium ciliatum (S. ciliatum) in China is 32.51 × 104 km2, the total suitable habitat area for Satyrium nepalense (S. nepalense) in China is 61.76 × 104 km2, and the area of the total suitable habitat for Satyrium yunnanense (S. yunnanense) in China is 89.73 × 104 km2. The potential suitable habitat of Satyrium is mainly distributed in Southwest China. The major environmental changes influencing the geographical distribution of S. ciliatum were temperature seasonality (Bio4), isothermality (Bio3), and mean temperature of coldest quarter (Bio11). The geographical distribution of S. nepalense was mainly affected by environmental variables like temperature seasonality (Bio4), isothermal environment (Bio3), and precipitation of the coldest quarter (Bio19); and the geographical distribution of the species S. yunnanense were mainly affected by the environmental variables such as temperature seasonality (Bio4), isothermality (Bio3) and lower temperature of the coldest month (Bio6). The distribution range of Satyrium’s extended with global warming increased, in both situations’ emissions of greenhouse gases with lower concentration (SSP1-2.6) and the emission of greenhouse gases with higher concentration (SSP5-8.5). According to the study, the distribution of suitable habitat would shift with change to higher elevated areas in the coming time.

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