scholarly journals A novel candidate species of Anaplasma that infects avian erythrocytes

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Ralph Eric Thijl Vanstreels ◽  
Michael J. Yabsley ◽  
Nola J. Parsons ◽  
Liandrie Swanepoel ◽  
Pierre A. Pistorius
Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 628
Author(s):  
Annette Herz ◽  
Eva Dingeldey ◽  
Camilla Englert

Parasitoids are currently considered for biological control of the spotted wing drosophila (SWD) in berry crops. Releases of mass-reared parasitoids require the presence of all resources necessary to ensure their effectiveness in the crop system. The use of floral resources to feed Trichopria drosophilae, one of the candidate species, was investigated in a laboratory study. The life expectancy of males and females increased by three to four times when they had access to flowers of buckwheat or of two cultivars of sweet alyssum. Female realized lifetime fecundity increased from 27 offspring/female exposed to water only to 69 offspring/female exposed to buckwheat flowers. According to this almost threefold increase in parasitoid fitness, it is advisable to introduce flowering plants into the crop system, when parasitoid releases are carried out. Sweet alyssum offers the advantage of not growing too tall in combination with an extended blooming. However, adult SWD were also able to feed on flowers of both plants and survived for at least 27 days, much longer than starving flies. The introduction of flowering plants to promote natural enemies therefore requires further consideration of the risk–benefit balance under field conditions to prevent unintended reinforcement of this pest.


PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0228483
Author(s):  
Akira Iguchi ◽  
Miyuki Nishijima ◽  
Yuki Yoshioka ◽  
Aika Miyagi ◽  
Ryuichi Miwa ◽  
...  

Zootaxa ◽  
2017 ◽  
Vol 4317 (2) ◽  
pp. 379
Author(s):  
MIGUEL VENCES ◽  
JÖRN KÖHLER ◽  
FRANK GLAW

We present molecular evidence for the presence of two species morphologically similar to Spinomantis bertini in Andohahela National Park, south-eastern Madagascar, differing by 5.5−6.3% pairwise DNA sequence divergences in the mitochondrial 16S rRNA gene. One of these was observed at higher elevations of ca. 1650 m above sea level, whereas the other was found at lower elevations of ca. 715 m a.s.l., close to the type locality of S. bertini (Isaka-Ivondro), and in one other location (Andreoky, ca. 1050 a.s.l.). We herein assign these low- to mid-elevation specimens to S. bertini based on their occurrence near the type locality and general agreement in colour pattern with the type specimen of Gephyromantis bertini Guibé, 1947. The high-elevation form is described as Spinomantis beckei sp. nov. based on its molecular divergence and reciprocal monophyly with respect to S. bertini, lower expression of greenish dorsal colour and less distinct frenal stripe. Based on a comparison of published call descriptions for S. bertini and our recordings of S. beckei, we hypothesize that S. bertini has a lower note repetition rate in advertisement calls. Molecular data suggest that the S. bertini species complex is more diverse than previously recognized, with at least two more candidate species identified: S. sp. Ca7 from Ranomafana National Park, and a newly identified candidate species S. sp. Ca12 from Pic d’Ivohibe Special Reserve. 


Aquaculture ◽  
2021 ◽  
pp. 737212
Author(s):  
Megarajan Sekar ◽  
Ritesh Ranjan ◽  
Biji Xavier ◽  
Shubhadeep Ghosh ◽  
Viji Pankyamma ◽  
...  
Keyword(s):  

2011 ◽  
Vol 286 (1) ◽  
pp. 30-37 ◽  
Author(s):  
D. M. Scott ◽  
F. Southgate ◽  
A. J. Overall ◽  
S. Waite ◽  
B. A. Tolhurst

Author(s):  
Jose Carranza-Rojas ◽  
Erick Mata-Montero

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of k , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research.


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