Aims
Our objectives are to examine the effects of hummock-depression spatial heterogeneity on plant communities and soil properties, and to understand the process of maintaining and adjusting microtopography-mediated hydrological inputs and their spatial fluctuations that produce obvious micro-habitats.
Methods
We set up 36 plots (1m×1m) and sampled 45 plant and 225 soil samples in flooded and non-flooded hummocks and depressions of the marshy, and the surrounding non-wetland meadows as well as in the Yellow River Source Zone, west China. We evaluated whether the alpine marshy wetland has a fertile-island effect by the comparison method.
Important Findings
Our results show that hummock presence can increase the spatial heterogeneity of the microhabitat and promote the plant diversity and soil fertility of the Kobresia tibetica community. Plant height, coverage, above-ground biomass, species richness and diversity were significantly higher in the flooded and non-flooded hummock microhabitat than in the areas between hummocks and surrounding non-wetland meadows. Compared with broad alpine meadows, the hummock-depression complex provided a microhabitat favourable to the growth of Cyperaceae. In the 0-50 cm soil layer, the closer the soil layer was to the ground surface, the higher its soil organic carbon and total nitrogen contents. Thus, in deeper layers, the gap between soil nutrients in wetland hummock-depression microhabitat and in the surrounding alpine meadows become smaller. Hence, the wetland hummock-depression microhabitat formed a fertile-island pattern. Therefore, these results contribute towards improving our understanding of ecosystem restoration in alpine marshy meadows.
Studies by grassland workers have shown that the occurrence of degradation indicator plants in grassland is an important sign of grassland degradation. The detection of degradation indicator plants can provide a certain data basis for the study of grassland degradation. In this paper, a target detection algorithm for improving YOLOv5 model is proposed to detect the degradation indicator plants (wolfsbane) in grassland. Firstly, the target detection dataset of the grassland degradation indicator plant(wolfsbane)is constructed, and then the backbone network is optimized by adding a coordinate attention mechanism on the basis of the original YOLOv5 model; The original feature pyramid module in the feature fusion module is replaced by a weighted bidirectional feature pyramid (BiFPN) network structure, which realizes effective weighted feature fusion and bi-directional cross-scale connection; A small target detection layer is also added to further improve the detection accuracy of small targets. Experimental results show that the proposed improved algorithm achieves an average precision (AP) of 80.4%, which is 3.4% better than the original YOLOv5 model, and verifies the effectiveness of the improved model for the detection of degraded indicator plants (wolfsbane).
Medicago archiducis-nicolai
Sirj. is a well-known high-quality forage as its good palatability and strong tolerance to drought, cold and saline-alkali stress. Here, the complete chloroplast genome sequence of
M. archiducis-nicolai
was reported. The size of the complete chloroplast genome is 127,072 bp in length. The chloroplast genome has no inverted repeat (IR) regions, which is very common in the family Fabaceae. The
M. archiducis-nicolai
chloroplast genome encodes 106 genes: 72 protein-coding genes, 30 tRNAs, and 4 rRNAs. The phylogenetic analysis result strongly suggested that
M. archiducis-nicolai
is a distinct lineage in
Medicago
, being sister to highly supported clade composed of three species (
M. hybrida, M. papillosa
and
M. sativa
).
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