Use of GIS to Prioritize Cogongrass (Imperata cylindrica) Control on Camp Shelby Joint Forces Training Center, Mississippi

2009 ◽  
Vol 2 (1) ◽  
pp. 74-82 ◽  
Author(s):  
Lisa Y. Yager ◽  
Matt Smith
Keyword(s):  
Invasive Species ◽  
Spatial Distribution ◽  
Control Strategies ◽  
Military Training ◽  
Imperata Cylindrica ◽  
Conservation Priorities ◽  
Training Center ◽  
Gis Analysis ◽  
Joint Forces ◽  
Reduction In Area

AbstractGeographic information systems (GIS) analysis considering size and spatial distribution of infestations of invasive species on a landbase can assist with developing appropriate control strategies for that species. We used GIS to evaluate strategies that placed highest priority on: smallest patches of cogongrass, largest patches of cogongrass, and cogongrass patches on land considered high-value under military training and conservation priorities on Camp Shelby Joint Forces Training Center (CSJFTC), MS. Strategies were first evaluated using predicted increase in area of new growth prevented, if prioritized patches were treated with herbicide. Travel and other time needed to implement strategies were then assessed as they affected total area treated. Assuming equivalent areas treated, predicted total reduction in area was consistently highest for the strategy prioritizing smallest patches and lowest for the strategy prioritizing largest patches. However, travel and other time was sufficiently reduced for the strategy prioritizing patches on high-value land compared to the other strategies to suggest that this strategy would result in the greatest reduction in area infested with cogongrass. Analyses of spatial distribution and size of infestations can assist land managers with selecting the appropriate strategy for controlling invasive species.

scholarly journals Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Yazmin Alcala-Canto ◽  
Juan Antonio Figueroa-Castillo ◽  
Froylán Ibarra-Velarde ◽  
Yolanda Vera-Montenegro ◽  
María Eugenia Cervantes-Valencia ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Variables ◽  
Control Strategies ◽  
Integrated Control ◽  
Area Under The Curve ◽  
Entropy Method ◽  
Distribution Model ◽  
Economic Losses ◽  
Precipitation Seasonality ◽  
Epidemiological Risk

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

scholarly journals WebGIS Based Poverty Level Analysis (Case Study Of Wonosari Sub-District Boalemo Regency)

2019 ◽  
Vol 1 (2) ◽  
pp. 77-86
Author(s):  
Irwan Muis ◽  
Sunarty Suly Eraku ◽  
Syahrizal Koem
Keyword(s):  
Spatial Distribution ◽  
Gis Analysis ◽  
Poverty Level ◽  
Gis Application ◽  
Household Poverty ◽  
Poor Households ◽  
Poverty Levels ◽  
Level Analysis ◽  
Descriptive Statistical Analysis

Information on household poverty level in Wonosari Sub-district area is still very difficult to access by all parties. Therefore, this study aims to analyze poverty level and map of the spatial distribution of webGIS-based poor households in the site area. In determining the number of samples, descriptive statistical analysis techniques focused on assessing and describing the poverty level of each household. GIS analysis used GIS Application 2.18 to map the spatial distribution of poor households and regional poverty levels. GIS Application has been equipped with 2 web tools that are able to display webGIS-based maps. The results shows that the poverty level of households is in the poor category with a percentage of 72% of households, 14% of households are in the extremely poor category and 14% are in the fairly poor category. and 1 village is in a fairly poor category. This is a village that was built with a view that can be accessed by various PCs, laptops and android media so that the maps information from an analysis of household poverty levels and the spatial distribution of poor households can be accessed on the webGIS that has been built.

The Global Expansion of Dengue: How Aedes aegypti Mosquitoes Enabled the First Pandemic Arbovirus

2020 ◽  
Vol 65 (1) ◽  
pp. 191-208 ◽  
Author(s):  
Oliver J. Brady ◽  
Simon I. Hay
Keyword(s):  
Invasive Species ◽  
Aedes Aegypti ◽  
Infectious Diseases ◽  
Control Strategies ◽  
Viral Disease ◽  
Rapid Rise ◽  
Disease Vector ◽  
Research Priority ◽  
Global Spread ◽  
Human Habitation

Dengue is an emerging viral disease principally transmitted by the Aedes ( Stegomyia) aegypti mosquito. It is one of the fastest-growing global infectious diseases, with 100–400 million new infections a year, and is now entrenched in a growing number of tropical megacities. Behind this rapid rise is the simple adaptation of Ae. aegypti to a new entomological niche carved out by human habitation. This review describes the expansion of dengue and explores how key changes in the ecology of Ae. aegypti allowed it to become a successful invasive species and highly efficient disease vector. We argue that characterizing geographic heterogeneity in mosquito bionomics will be a key research priority that will enable us to better understand future dengue risk and design control strategies to reverse its global spread.

scholarly journals Low-Cost Archaeological Investigation and Rapid Mapping of Ancient Stone Tidal Weirs in the Penghu Archipelago Using Google Earth

2019 ◽  
Vol 11 (17) ◽  
pp. 4536 ◽  
Author(s):  
Lei Luo ◽  
Xinyuan Wang ◽  
Jie Liu ◽  
Wenwu Zheng ◽  
Jing Zhen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Spatial Distribution ◽  
Low Cost ◽  
Google Earth ◽  
Gis Analysis ◽  
Archaeological Investigation ◽  
Rapid Mapping ◽  
The Taiwan Strait ◽  
Very High

This paper provides a brief history review of the use of ancient weirs in fishing on our planet, as well as a pilot study that involves investigating and mapping the coastal heritage of ancient stone tidal weirs (STWs) in the Penghu Archipelago which is located in the Taiwan Strait. The spatial distribution and morphological features of STWs across Penghu Archipelago were investigated and analyzed using very high-resolution (VHR) and freely available Google Earth (GE) imagery and geographic information system (GIS) analysis tools. A total of 539 ground-truthed STWs were identified from multiple temporal GE images, and these accounted for over 90% of the localized inventory databases. The proposed GE-based method was found to be more efficient, timely and effective compared to field and airborne surveys. This paper illustrates the utility of GE as a source of freely available VHR remote sensing imagery for archaeological surveys and heritage sustainability in coastal areas.

Examining Local Transferability of Predictive Species Distribution Models for Invasive Plants: An Example with Cogongrass (Imperata cylindrica)

2011 ◽  
Vol 4 (4) ◽  
pp. 390-401 ◽  
Author(s):  
Gary N. Ervin ◽  
D. Christopher Holly
Keyword(s):  
Invasive Species ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Imperata Cylindrica ◽  
Environmental Data ◽  
Training Data ◽  
Distribution Data ◽  
Strongly Correlated ◽  
Distribution Models ◽  
Tree Canopy Cover

AbstractSpecies distribution modeling is a tool that is gaining widespread use in the projection of future distributions of invasive species and has important potential as a tool for monitoring invasive species spread. However, the transferability of models from one area to another has been inadequately investigated. This study aimed to determine the degree to which species distribution models (SDMs) for cogongrass, developed with distribution data from Mississippi (USA), could be applied to a similar area in neighboring Alabama. Cogongrass distribution data collected in Mississippi were used to train an SDM that was then tested for accuracy and transferability with cogongrass distribution data collected by a forest management company in Alabama. Analyses indicated the SDM had a relatively high predictive ability within the region of the training data but had poor transferability to the Alabama data. Analysis of the Alabama data, via independent SDM development, indicated that predicted cogongrass distribution in Alabama was more strongly correlated with soil variables than was the case in Mississippi, where the SDM was most strongly correlated with tree canopy cover. Results suggest that model transferability is influenced strongly by (1) data collection methods, (2) landscape context of the survey data, and (3) variations in qualitative aspects of environmental data used in model development.

scholarly journals Evaluation of Methicillin-Resistant Staphylococcus aureus Skin and Soft-Tissue Infection Prevention Strategies at a Military Training Center

2013 ◽  
Vol 34 (8) ◽  
pp. 841-843 ◽  
Author(s):  
Stephanie M. Morrison ◽  
Carl R. Blaesing ◽  
Eugene V. Millar ◽  
Uzo Chukwuma ◽  
Carey D. Schlett ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
High Risk ◽  
Soft Tissue ◽  
Infection Prevention ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Military Training ◽  
Soft Tissue Infections ◽  
Training Center ◽  
Prevention Strategies ◽  
Methicillin Resistant

Military trainees are at high risk for skin and soft-tissue infections (SSTIs), especially those caused by methicillin-resistant Staphylococcus aureus (MRSA). A multicomponent hygiene-based SSTI prevention strategy was implemented at a military training center. After implementation, we observed 30% and 64% reductions in overall and MRSA-associated SSTI rates, respectively.

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