In reservoirs or lakes, mixing depth affects growth and loss rates of phytoplankton populations. Based on 1-year data from the Zeya reservoir, China, we scaled the mixing depth throughout a whole year by utilizing cluster analysis, and then investigated its influence on phytoplankton dynamics and other physical and chemical parameters. Over the whole year, all physical and chemical parameters except TN and temperature had significant correlations with mixing depth, indicating that mixing depth is one of the important driving factors influencing water environment. According to mixing depth, a year can be divided into three different periods, including the thermally stratified period, isothermally mixed period, and transition period between them. When considering the former two different periods separately, mixing depth had no correlation with the phytoplankton biovolume. However, over the whole year a significant correlation was observed, which indicated that the influence of mixing depth on phytoplankton growth in the Zeya reservoir still followed Diehl's theory. Furthermore, according to the steady-state assumption, a unimodal curve (mixing depthphytoplankton biovolume) with a significant peak appearing at a mixing depth of 2 m was observed, closely agreeing with Diehl' prediction.
Grassland plays a key role in human production and life, especially in the protection and improvement of the natural environment, which cannot be replaced by other ecosystems, such as maintaining water and soil, preventing wind and sand fixation, maintaining carbon balance, affecting climate change, and producing biological products,.. More importantly, contemporary society attaches great importance to the development of agriculture and animal husbandry. Protecting and nurturing grassland plants and animals, maintaining biodiversity, rational grazing, and maintaining the sustainable development of the grassland ecological environment have become the top priorities. In view of the current serious grassland degradation and the decline of livestock carrying capacity, this paper proposes a grassland environmental monitoring system based on the ZigBee wireless sensor network. The system consists of a grassland wireless monitoring network and a remote PC, which realizes real-time and remote monitoring of environmental information, such as air temperature and humidity, light intensity, and rainfall that affect the growth of grassland pastures. Based on the requirements of the agricultural field data monitoring system, the overall framework of the system was designed and built. The system mainly includes two parts: the ZigBee wireless sensor network subsystem and the remote management software subsystem, and data communication is realized between the two through the Ethernet system data exchange protocol. Among them, the ZigBee wireless sensor network subsystem is deployed in the grassland area and mainly realizes the functions of real-time collection, processing, and wireless transmission of grassland data. The remote management software subsystem is mainly used for data reception, storage, and display and can maintain communication with the gateway node to support real-time monitoring of grassland data by remote browsers.
In the case of increasing fragmentation of wetlands, the study of the relationship between wetland landscape characteristics and total nitrogen (TN) in water is of great significance to reveal the mechanism of wetland water purification. Taking the Naoli River (NR) wetlands in Northeast China as the research object, 10 uniformly distributed sampling sites in the study area were sampled in August 2015 to test the TN concentration and interpret the images of NR wetlands in the same period. Taking the sampling site as the control point, the whole wetlands were divided into 10 regions, and the landscape index of each region was extracted. In order to reveal whether the landscape characteristics are related to the TN concentration in the wetlands water body, the landscape index and the TN concentration in the control point water body were analyzed by correlation analysis, step-by-step elimination analysis and path analysis to reveal whether the landscape characteristics are related to the TN concentration under wetlands receiving agricultural drainages. The results showed that the correlation coefficients between four area indexes or eight shape indexes and TN concentration did not reach a significant correlation level (P > 0.05), indicating that TN removal was not only determined by a single landscape index. The path coefficient of edge density (ED) index is-0.41, indicating that wetland patch connectivity is the primary factor of TN removal, and there is no relationship between the larger patch area and the higher TN removal. The removal of TN in wetlands is restricted by the synergistic effect of landscape area and shape characteristics.
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