The Amazon and Its Biodiversity: a Source of Unexplored Potential Natural Enemies for Biological Control (predators and Parasitoids)
Neotropical entomology(2023)
Embrapa Recursos Genéticos e Biotecnologia | Embrapa Cerrados | Embrapa Amapá
Abstract
The Amazon is an important source of natural enemies for biological control. The diversity of biocontrol agents in the Amazon is considerably higher than that in other Brazilian regions. However, few studies have focused on the bioprospecting of natural enemies in the Amazon. Furthermore, the expansion of agricultural land in recent decades has caused biodiversity loss in the region, including the loss of potential biocontrol agents, due to the replacement of native forests with cultivated areas and forest degradation. In this study, we reviewed the main groups of natural enemies in the Brazilian Legal Amazon: predatory mites (mainly Acari: Phytoseiidae), ladybirds (Coleoptera: Coccinellidae), and social wasps (Hymenoptera: Vespidae: Polistinae) and the Hymenoptera parasitoids of eggs (Trichogrammatidae) and of frugivorous larvae (Braconidae and Figitidae). The main species prospected and used in biological control are presented. The lack of knowledge and perspectives regarding these groups of natural enemies as well as the challenges of conducting research in the Amazon is discussed.
MoreTranslated text
Key words
Phytoseiidae,Coccinellidae,Polistinae,Trichogrammatidae,Braconidae,Figitidae
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
FRONTIERS IN PLANT SCIENCE 2023
被引用6
Agronomy 2024
被引用0
Detection of Wildlife Species in the Peruvian Amazon Using Transfer Learning.
COMPUTACION Y SISTEMAS 2024
被引用0
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper