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Published on: May 20, 2018
The development of high-density aggregation spatial distribution patterns under high stress
Kangkang Mi1, Jiejun Li2, Xiaoge Tian3
1Department of Forestry, Agricultural College, Shihezi University, Shihezi, Xinjiang, China.
Abstract:
In high-stress environments such as arid deserts, plant populations often adapt to harsh conditions by forming spatial patterns of high-density aggregation. However, most studies have focused on the static description of spatial patterns or the correlation analysis at a single time point, lacking long-term continuous observations on how high-density aggregation patterns gradually form and develop over time. Focusing on Haloxylon ammodendron in the Gurbantunggut Desert, we conducted five consecutive years of field surveys and spatial analyses to investigate how its aggregation pattern develops under wind erosion stress. Research has found that in the early stage of growth, the population of H. ammodendron forms a stable structure through high-density aggregation. As the population ages, it exhibits a pattern of gradual expansion outward from the fulcrum, with the direction of expansion being largely consistent with the main wind direction (northwest). The Random Forest model (RF) and the Generalized Linear Mixed Model (GLMM) indicate that density, wind speed, and neighbor effect are the key factors affecting population survival and spatial expansion. Wind speed modulated directional survival, shaping spatial occupancy, while neighbor effects adjusted population structure to facilitate stable expansion. Further research reveals that H. ammodendron actively constructs a microenvironment through self-organizing behavior, not only alleviating wind erosion stress but also achieving the expansion of ecological niches rather than the contraction as traditionally believed. This study highlights the significance of biological interactions and environmental stress jointly driving the spatial self-organization of vegetation, providing a new perspective for understanding the adaptation mechanisms of plant populations in extreme environments.
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