Community Classification of Piñon-Juniper Vegetation in the Four Corners Region, USA

2020 ◽  
Vol 66 (6) ◽  
pp. 687-699
Author(s):  
Gennaro Falco ◽  
Kristen M Waring
Keyword(s):  
United States ◽  
Classification System ◽  
The United States ◽  
Tree Regeneration ◽  
Stand Age ◽  
Community Type ◽  
Data Set ◽  
Precipitation Patterns ◽  
Four Corners ◽  
Community Types

Abstract Piñon-juniper is one of the most common vegetation types in the Four Corners states of the western United States (Arizona, Colorado, New Mexico, and Utah). Because of its high degree of community heterogeneity across the landscape, development of a more detailed and statistically supported classification system for piñon-juniper has been requested by regional land managers. We used a USDA Forest Service Forest Inventory and Analysis (FIA) data set from the Four Corners states to develop a statistics-based classification system for piñon-juniper vegetation. Cluster analysis was used to group piñon-juniper FIA data into community classes. Classification and regression tree analysis was then used to develop a model for predicting piñon-juniper community types. To determine which variables contributed most to classifying piñon-juniper FIA data, a random forest analysis was conducted. Results from these analyses support a six-class piñon-juniper community-type model within the Four Corners states. Using the classification tree, membership of FIA piñon-juniper communities can be accurately predicted (r2 = 0.81) using only relative overstory species abundance. Our dominance-based classification system was useful in classifying piñon-juniper community types and could be used in the field to identify broad community types and complement more refined tools available for stand-scale decisionmaking. Study Implications: Piñon-juniper vegetation communities commonly occur in the Four Corners region of the United States. We used a regional data set to develop a statistically based classification system for piñon-juniper communities. We found support for a dominance-based approach supporting initial classification into six community classes. Classes were based on different overstory species dominance patterns, stand structural characteristics (stand density index, basal area [square meters per hectare], trees per hectare, and stand age), and precipitation patterns (mean annual precipitation and monsoonal index) (Table S2). Community type can be predicted using relative overstory abundance to help managers prioritize regional areas (~6,000 acres [2,428 hectares]) for management and predict responses based on precipitation patterns, current understory tree regeneration, and plant community abundance. This system could lead to better planning documents and management decisions on a regional scale to complement more refined tools available for stand-scale management such as plant associations and detailed soil maps.

International Research and Variation in Views of Ethnicity

2012 ◽  
Vol 2 (2) ◽  
pp. 66-72
Author(s):  
Ella Inglebret ◽  
Amy Skinder-Meredith ◽  
Shana Bailey ◽  
Carla Jones ◽  
Ashley France
Keyword(s):  
United States ◽  
Classification System ◽  
International Research ◽  
The United States ◽  
Research Articles ◽  
Journal Articles ◽  
Research Participants ◽  
The Past ◽  
International Scale ◽  
Publication Patterns

The authors in this article first identify the extent to which research articles published in three American Speech-Language-Hearing Association (ASHA) journals included participants, age birth to 18 years, from international backgrounds (i.e., residence outside of the United States), and go on to describe associated publication patterns over the past 12 years. These patterns then provide a context for examining variation in the conceptualization of ethnicity on an international scale. Further, the authors examine terminology and categories used by 11 countries where research participants resided. Each country uses a unique classification system. Thus, it can be expected that descriptions of the ethnic characteristics of international participants involved in research published in ASHA journal articles will widely vary.

Planting native trees to restore riparian forests increases biotic resistance to non-native plant invasions

2021 ◽  
pp. 1-24
Author(s):  
Chad F. Hammer ◽  
John S. Gunn
Keyword(s):  
United States ◽  
Ecosystem Service ◽  
Invasive Plant ◽  
Biotic Resistance ◽  
The United States ◽  
Tree Regeneration ◽  
Tree Planting ◽  
Plant Colonization ◽  
Native Plant ◽  
Native Trees

Abstract Non-native invasive plant species are a major cause of ecosystem degradation and impairment of ecosystem service benefits in the United States. Forested riparian areas provide many ecosystem service benefits and are vital to maintaining water quality of streams and rivers. These systems are also vulnerable to natural disturbances and invasion by non-native plants. We assessed whether planting native trees on disturbed riparian sites may increase biotic resistance to invasive plant establishment in central Vermont in the northeastern United States. The density (stems/m2) of invasive stems was higher in non-planted sites (x̄=4.1 stems/m2) compared to planted sites (x̄=1.3 stems/m2). More than 90% of the invasive plants were Japanese knotweed (Fallopia japonica). There were no significant differences in total stem density of native vegetation between planted and non-planted sites. Other measured response variables such as native tree regeneration, species diversity, soil properties and soil function showed no significant differences or trends in the paired riparian study sites. The results of this case study indicate that tree planting in disturbed riparian forest areas may assist conservation efforts by minimizing the risk of invasive plant colonization.

scholarly journals Altitude and risk of sudden unexpected infant death in the United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Johnston ◽  
Xiaohan Yan ◽  
Tatiana M. Anderson ◽  
Edwin A. Mitchell
Keyword(s):  
United States ◽  
Logistic Regression ◽  
Infant Death ◽  
The United States ◽  
Sudden Infant ◽  
Data Set ◽  
Live Births ◽  
Sudden Unexpected Infant Death ◽  
Increased Risk ◽  
Unexpected Infant Death

AbstractThe effect of altitude on the risk of sudden infant death syndrome (SIDS) has been reported previously, but with conflicting findings. We aimed to examine whether the risk of sudden unexpected infant death (SUID) varies with altitude in the United States. Data from the Centers for Disease Control and Prevention (CDC)’s Cohort Linked Birth/Infant Death Data Set for births between 2005 and 2010 were examined. County of birth was used to estimate altitude. Logistic regression and Generalized Additive Model (GAM) were used, adjusting for year, mother’s race, Hispanic origin, marital status, age, education and smoking, father’s age and race, number of prenatal visits, plurality, live birth order, and infant’s sex, birthweight and gestation. There were 25,305,778 live births over the 6-year study period. The total number of deaths from SUID in this period were 23,673 (rate = 0.94/1000 live births). In the logistic regression model there was a small, but statistically significant, increased risk of SUID associated with birth at > 8000 feet compared with < 6000 feet (aOR = 1.93; 95% CI 1.00–3.71). The GAM showed a similar increased risk over 8000 feet, but this was not statistically significant. Only 9245 (0.037%) of mothers gave birth at > 8000 feet during the study period and 10 deaths (0.042%) were attributed to SUID. The number of SUID deaths at this altitude in the United States is very small (10 deaths in 6 years).

scholarly journals Development of a semi-parametric PAR (Photosynthetically Active Radiation) partitioning model for the United States, version 1.0

2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law
Keyword(s):  
United States ◽  
Elevation Angle ◽  
Model Performance ◽  
Diffuse Radiation ◽  
The United States ◽  
Polynomial Model ◽  
Coefficient Of Determination ◽  
Data Set ◽  
Cubic Polynomial ◽  
Solar Elevation Angle

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.

Racial Sentiment and Public Support for Arming Teachers with Guns in the United States

2021 ◽  
pp. 215336872110389
Author(s):  
Andrew J. Baranauskas
Keyword(s):  
United States ◽  
African Americans ◽  
Minority Groups ◽  
Public Support ◽  
The United States ◽  
Data Set ◽  
Racial Issue ◽  
Racial Resentment ◽  
Nationally Representative ◽  
Negative Feelings

In the effort to prevent school shootings in the United States, policies that aim to arm teachers with guns have received considerable attention. Recent research on public support for these policies finds that African Americans are substantially less likely to support them, indicating that support for arming teachers is a racial issue. Given the racialized nature of support for punitive crime policies in the United States, it is possible that racial sentiment shapes support for arming teachers as well. This study aims to determine the association between two types of racial sentiment—explicit negative feelings toward racial/ethnic minority groups and racial resentment—and support for arming teachers using a nationally representative data set. While explicit negative feelings toward African Americans and Hispanics are not associated with support for arming teachers, those with racial resentments are significantly more likely to support arming teachers. Racial resentment also weakens the effect of other variables found to be associated with support for arming teachers, including conservative ideology and economic pessimism. Implications for policy and research are discussed.

Septic shock and systemic inflammatory response syndrome patients' CD15+ granulocytes were subjected to global transcriptional profiling (SIRS)

2021 ◽  
Author(s):  
Marni Mack ◽  
Argo Easston
Keyword(s):  
Gene Expression ◽  
United States ◽  
Septic Shock ◽  
Immune Cells ◽  
Transcriptional Profiling ◽  
The United States ◽  
Transcriptional Level ◽  
Data Set ◽  
Transcriptional Alterations ◽  
Level I

In the United States, sepsis, the body's response to infection in a typically sterile circulation, is a leading causeof death (1). To assess the primary transcriptional alterations associated with each illness state, I utilized amicroarray data set from a cohort of thirtyone individuals with septic shock or systemic inflammatory responsesyndrome (2). At the transcriptional level, I discovered that the granulocytes of patients with SIRS weresimilar to those of patients with septic shock. SIRS showed a “intermediate” gene expression state betweenthat of control patients and that of septic shock patients for numerous genes expressed in the granulocyte. Thediscovery of the most differentially expressed genes in the granulocytic immune cells of patients with septicshock might aid the development of new therapies or diagnostics for an illness with a 14.7 percent to 29.9% inhospitaldeath rate despite decades of study (1).

A Postlandfall Hurricane Classification System for the United States

2006 ◽  
Vol 225 ◽  
pp. 1025-1034 ◽  
Author(s):  
Jason Carl Senkbeil ◽  
Scott Christopher Sheridan
Keyword(s):  
United States ◽  
Classification System ◽  
The United States

Legislative Accomplishment and Policy Issue Substance

2013 ◽  
Author(s):  
John S. Lapinski
Keyword(s):  
United States ◽  
Substance P ◽  
Political Behavior ◽  
Policy Issue ◽  
The United States ◽  
Legislative Behavior ◽  
Aggregate Level ◽  
Data Set ◽  
Proper Understanding ◽  
Specific Policy

This chapter introduces a new measure of legislative accomplishment. To understand lawmaking requires that one move beyond studying political behavior in Congress alone and beyond a complete empirical reliance on roll call votes. Moreover, legislative behavior and legislative outputs must be studied in tandem to gain a proper understanding of the lawmaking process in the United States. Although the idea of studying important lawmaking across time is not controversial, constructing an appropriate measure is not a trivial exercise. The chapter constructs a comprehensive lawmaking data set that provides measures of legislative accomplishment at the aggregate level as well as by specific policy issue areas for a 118-year period. It also explains the construction of Congress-by-Congress measures of legislative accomplishment, including measures broken down by the policy-coding schema.

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