Distribution Of Algae Species Research Articles

ОПЫТ КАРТОГРАФИРОВАНИЯ ДОННОЙ РАСТИТЕЛЬНОСТИ (НА ПРИМЕРЕ БУХТЫ ЛАСПИ, ЧЁРНОЕ МОРЕ)

The article covers the possibility of applying digital technologies for mapping seafloor vegetation for coastal sea zone. Submitted method allows promptly and accurately receive information about distribution of algae species. Laspi bay is distinguished by biological diversity, an abundance of unique habitats of seafloor vegetation, where sea grass and algae communities are represented. Based on these qualities it was chosen as a model region for mapping macrophytes distribution. Aerial photography using an unmanned aerial vehicle (UAV) and hydro-botanical studies were conducted in the summer of 2019 year. The distribution map of macrophyte made based on aerial photos, while composition and structure were determined though hydro-botanical surveys. Five transects were laid in the bay, hydrobotanical profiles were compiled. Five seafloor plant communities identified for mapping. Digitized boundaries were set using software package QGIS version 2.18.12. Based on boundaries distribution map was made. The spatial patterns of the distributionof dominant macrophyte species (Cystoseira, Phyllophora and Zostera noltei) mapped along with quantitative characteristics.

Fuzzy Self-Tuning PID-Based Intelligent Control of an Anti-Wave Buoy Data Acquisition Control System

In aquaculture, water quality is influenced by excessive feeding, a high breeding density, the species composition and the distribution of algae species. Traditional buoys can only collect water quality data at a fixed depth, and it is impossible to measure the water quality at different depths in the water column. Sea waves are common in the open ocean and influence data acquisition systems via wave forces, which affect the accuracy of data collection. Considering the above problems, a data acquisition control system with automatic lifting is designed. The underwater acquisition system collects water quality data and sends the data to a microcontroller. The microcontroller sends a displacement control signal to a PLC according to the processed data. The PLC automatically develops the corresponding acceleration and deceleration operating curves according to the displacement. A fuzzy PID self-tuning control method is used to accurately control the speed and steering of the stepping motor, and an IIR digital filter is designed to reduce the interference from sea waves. The simulation results show that the stepping motor responds quickly, the speed of the stepping motor is stable, and the data acquisition time is reduced based on the proposed algorithm. Moreover, wave interference is largely mitigated, and the system is generally stable.