The Geographical Distribution of Fish in the United States

1875 ◽  
Vol 7 ◽  
pp. 93
Author(s):  
Robert B. Roosevelt
Keyword(s):  
United States ◽  
Geographical Distribution ◽  
The United States ◽  
Distribution Of Fish

Uromyces appendiculatus. [Descriptions of Fungi and Bacteria].

1965 ◽  
Author(s):  
G. F. Laundon
Keyword(s):  
United States ◽  
Sierra Leone ◽  
Geographical Distribution ◽  
World Wide ◽  
Indirect Evidence ◽  
Severe Infection ◽  
The United States ◽  
Total Loss ◽  
Uromyces Appendiculatus

Abstract A description is provided for Uromyces appendiculatus. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: On Dolichos, Phaseolus and Vigna species. DISEASE: Rust on leaves of French, Lima, and Scarlet Runner beans, and other Phaseolus spp., and cowpeas. The reddish-brown, circular sori may be surrounded by a yellow halo in some varieties. Complete defoliation and total loss of crop results in seasons favouring severe infection. GEOGRAPHICAL DISTRIBUTION: World-wide wherever beans are grown (CMI Map 290, Ed. 2, 1964). TRANSMISSION: By urediospores disseminated by wind, and through contact with animals including man and his implements. Indirect evidence of the possibility of introduction into Sierra Leone on seed imported from Ghana and S. Africa has been given by Deighton (25: 253). Some 40% of urediospores stored for 2 yr. at -60°C, and 16% stored more than 600 days at -18°C, have survived with virulence unimpaired, and it is thought that the rust is thus able to overwinter on bean trash and trellis poles in the United States (42: 167; 43, 299).

scholarly journals Geographical Distribution of Fungal Plant Pathogens in Dust Across the United States

2019 ◽  
Vol 7 ◽  
Author(s):  
Kristin Dietzel ◽  
Denis Valle ◽  
Noah Fierer ◽  
Jana M. U'Ren ◽  
Albert Barberán
Keyword(s):  
United States ◽  
Geographical Distribution ◽  
Plant Pathogens ◽  
The United States ◽  
Fungal Plant Pathogens

scholarly journals Application of Epidemiological Geographic Information System: An Open-Source Spatial Analysis Tool Based on the OMOP Common Data Model

2020 ◽  
Vol 17 (21) ◽  
pp. 7824
Author(s):  
Jaehyeong Cho ◽  
Seng Chan You ◽  
Seongwon Lee ◽  
DongSu Park ◽  
Bumhee Park ◽  
...  
Keyword(s):  
United States ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Analysis ◽  
Health Outcomes ◽  
Open Source ◽  
Geographical Distribution ◽  
The United States ◽  
Geographic Information ◽  
Common Data Model

Background: Spatial epidemiology is used to evaluate geographical variations and disparities in health outcomes; however, constructing geographic statistical models requires a labor-intensive process that limits the overall utility. We developed an open-source software for spatial epidemiological analysis and demonstrated its applicability and quality. Methods: Based on standardized geocode and observational health data, the Application of Epidemiological Geographic Information System (AEGIS) provides two spatial analysis methods: disease mapping and detecting clustered medical conditions and outcomes. The AEGIS assesses the geographical distribution of incidences and health outcomes in Korea and the United States, specifically incidence of cancers and their mortality rates, endemic malarial areas, and heart diseases (only the United States). Results: The AEGIS-generated spatial distribution of incident cancer in Korea was consistent with previous reports. The incidence of liver cancer in women with the highest Moran’s I (0.44; p < 0.001) was 17.4 (10.3–26.9). The malarial endemic cluster was identified in Paju-si, Korea (p < 0.001). When the AEGIS was applied to the database of the United States, a heart disease cluster was appropriately identified (p < 0.001). Conclusions: As an open-source, cross-country, spatial analytics solution, AEGIS may globally assess the differences in geographical distribution of health outcomes through the use of standardized geocode and observational health databases.

scholarly journals Similarity, Pattern, and Grouping of Soybean Fungal Diseases in the United States: Implications for the Risk of Soybean Rust

Plant Disease ◽  
2009 ◽  
Vol 93 (2) ◽  
pp. 162-169 ◽  
Author(s):  
X. Li ◽  
X. B. Yang
Keyword(s):  
United States ◽  
Downy Mildew ◽  
Geographical Distribution ◽  
Leaf Spot ◽  
The United States ◽  
Fungal Diseases ◽  
Brown Spot ◽  
Soybean Rust ◽  
Yield Losses ◽  
Similarity Coefficients

Ten biological or ecological characteristics of pathogens/diseases were used to quantitatively describe 34 soybean (Glycine max) fungal diseases in the United States. These characteristics included optimal temperatures for disease development, host ranges, characteristics of disease cycle, and the pathogens' survival capacity. Gower's general similarity coefficients for pairs of diseases were determined and used in principal coordinate analysis (PCoA) to project the diseases into a two-dimensional space, in which significant patterns were identified for some of the characteristic variables, e.g., means of pathogen dispersal. Similarity coefficients indicated that soybean rust (Phakopsora pachyrhizi) resembled soybean downy mildew (Peronospora manshurica) and Leptosphaerulina leaf spot (Leptosphaerulina trifolii). Cluster analysis with multiscale bootstrapping identified two major clusters with high significance level (P > 0.95). In a loose cluster (P = 0.86), soybean rust was grouped with brown spot (Septoria glycines), frogeye leaf spot (Cercospora sojina), Phyllosticta leaf spot (Phyllosticta sojicola), purple seed stain (Cercospora kikuchii), downy mildew, and Leptosphaerulina leaf spot. Estimated soybean yield losses in the United States from 1996 to 2005 and the geographical distribution information of the diseases in this cluster implied that the potential geographical distribution range of soybean rust may include most U.S. soybean production regions and that yield losses would be light in the north but moderate in the south if environmental conditions are conducive.

Sign in / Sign up

Export Citation Format

Share Document