scholarly journals Assessment of Current Status of Invasive Aquatic Plants in Louisiana

OALib ◽  
2020 ◽  
Vol 07 (06) ◽  
pp. 1-10
Author(s):  
F. A. Anifowose ◽  
V. I. Fagorite
2020 ◽  
Vol 39 (3) ◽  
pp. 521-533 ◽  
Author(s):  
Lauren M. Kuehne ◽  
Carl O. Ostberg ◽  
Dorothy M. Chase ◽  
Jeffrey J. Duda ◽  
Julian D. Olden

Author(s):  
Luana Santos ◽  
Fernanda Silva ◽  
Lidiane Santos ◽  
Ingred Carregosa ◽  
Alberto Wisniewski Jr.

2008 ◽  
Vol 32 (2) ◽  
pp. 140-145 ◽  
Author(s):  
W. James Catallo ◽  
Todd F. Shupe ◽  
Thomas L. Eberhardt

2021 ◽  
Vol 13 (4) ◽  
pp. 582
Author(s):  
Erik A. Bolch ◽  
Erin L. Hestir ◽  
Shruti Khanna

Invasive plants are non-native species that can spread rapidly, leading to detrimental economic, ecological, or environmental impact. In aquatic systems such as the Sacramento-San Joaquin River Delta in California, USA, management agencies use manned aerial vehicles (MAV) imaging spectroscopy missions to map and track annual changes in invasive aquatic plants. Advances in unmanned aerial vehicles (UAV) and sensor miniaturization are enabling higher spatial resolution species mapping, which is promising for early detection of invasions before they spread over larger areas. This study compared maps made from UAV-based imaging spectroscopy with the manned airborne imaging spectroscopy-derived maps that are currently produced for monitoring invasive aquatic plants in the Sacramento-San Joaquin Delta. Concurrent imagery was collected using the MAV mounted HyMap sensor and the UAV mounted Nano-Hyperspec at a wetland study site and classification maps generated using random forest models were compared. Classification accuracies were comparable between the Nano- and HyMap-derived maps, with the Nano-derived map having a slightly higher overall accuracy. Additionally, the higher resolution of the Nano imagery allowed detection of patches of water hyacinth present in the study site that the HyMap could not. However, it would not be feasible to operate the Nano as a replacement to HyMap at scale despite its improved detection capabilities due to the high costs associated with overcoming area coverage limitations. Overall, UAV-based imaging spectroscopy provides comparable or improved capability, and we suggest it could be used to supplement existing monitoring programs by focusing on target areas of high ecologic or economic priority.


2021 ◽  
Author(s):  
Shakira Stephanie Elaine Azan

The purpose of the research was to clarify the common traits of a successful aquatic invasive plant. The biological traits of aquatic plants sold by aquarium and ornamental pond stores in the Greater Toronto Area, Ontario were analysed using logistic regression analyses (LRM). The multinomial LRM successfully predicts group identity 63% of the time, clearly differentiating native invasive and native non invasive from alien invasive (SI), but not ailen non invasive (ANI) from AI. In contrast, the binomial LRM effectively discriminates ANI from AI taxa 77% of the time. The variable that best discriminated between AI and ANI are type of propagation strategies, number of propagation strategies used, number of dispersal mechanisms used, minimum temperature, and sales volume of aquatic plants as a proxy for introduction. Recognizing the common traits of successful invaders allows for the identification of ANI taxa that have the potential to become invaders, prior to introduction, thus preventing future invasions.


2021 ◽  
Author(s):  
Shakira Stephanie Elaine Azan

The purpose of the research was to clarify the common traits of a successful aquatic invasive plant. The biological traits of aquatic plants sold by aquarium and ornamental pond stores in the Greater Toronto Area, Ontario were analysed using logistic regression analyses (LRM). The multinomial LRM successfully predicts group identity 63% of the time, clearly differentiating native invasive and native non invasive from alien invasive (SI), but not ailen non invasive (ANI) from AI. In contrast, the binomial LRM effectively discriminates ANI from AI taxa 77% of the time. The variable that best discriminated between AI and ANI are type of propagation strategies, number of propagation strategies used, number of dispersal mechanisms used, minimum temperature, and sales volume of aquatic plants as a proxy for introduction. Recognizing the common traits of successful invaders allows for the identification of ANI taxa that have the potential to become invaders, prior to introduction, thus preventing future invasions.


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