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西伯利亚鹤对鄱阳湖不同水位水文变化及觅食栖息地可利用性的响应

Response of Siberian Cranes () to Hydrological Changes and the Availability of Foraging Habitat at Various Water Levels in Poyang Lake.

作者信息

Shao Mingqin, Wang Jianying, Ding Hongxiu, Yang Fucheng

机构信息

School of Life Sciences, Jiangxi Normal University, Nanchang 330022, China.

出版信息

Animals (Basel). 2024 Jan 11;14(2):234. doi: 10.3390/ani14020234.

DOI:10.3390/ani14020234
PMID:38254403
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10812764/
Abstract

To assess the Siberian crane ()'s response to changing water levels and habitat quality at Poyang Lake, we analyzed the lake's hydrological trends over the past two decades with the Mann-Kendall and Sen slope methods. Additionally, we explored the link between the crane population size and hydrological conditions at the lake from 2011 to 2019. Meanwhile, five environmental factors, including habitat type, distance from shallow lakes, human footprint index, elevation and normalized vegetation index were selected, and the distribution patterns of suitable habitats for the Siberian crane under 10 water level gradients with intervals of about 1 m (5.3-14.2 m) were simulated by using an improved habitat suitability index model that determines the weights of evaluating factors based on the MaxEnt model. The results showed that the overall trend of the inundated area in Poyang Lake was shrinking in the last 20 years, with a significant increase in the area of exposed floodland during the early wintering period (Z = -2.26). The prolonged drought resulting from this will force vegetation succession, thereby diminishing the food resources for cranes in their natural habitat. The mean inundated area in June demonstrated a significant negative correlation with the population of Siberian cranes in natural habitats ( = -0.75, = 0.02). Shortage of the Siberian crane-preferred tuber due to June flooding was the primary driver of the crane's altered foraging strategy and habitat shift. In years with relatively normal June inundation, indicating abundant resources, the relationship between the inundated area during the dry season and the crane population fit well, with a quadratic curve ( = 0.92, = 0.02). The dry season's inundated area primarily affected the crane population and distribution pattern by influencing the availability of food resources, and both excessive and insufficient inundation areas were unfavorable for crane survival. The modeling results for habitat suitability indicated that as the water level decreased, the trend of the area of good habitat for the Siberian crane showed an inverted bell shape, peaking at a water level of 8.8 m, with optimal conditions occurring between 8 and 10 m. The combined effects of climate and human activities have made the shortage of food resources in Poyang Lake the new normal. The degradation of natural habitats has led to a decline in the quality of Siberian crane habitats, and artificial habitats can only be used as refuges to a certain extent. Thus, formulating strategies to restore natural habitats and enhance the management of artificial habitats is crucial for the conservation efforts of Siberian cranes.

摘要

为评估白鹤对鄱阳湖水位变化和栖息地质量的响应,我们采用曼-肯德尔法和森斜率法分析了该湖过去二十年的水文趋势。此外,我们还探究了2011年至2019年期间白鹤种群数量与该湖水文状况之间的联系。同时,选取了包括栖息地类型、距浅湖距离、人类足迹指数、海拔和归一化植被指数在内的五个环境因素,并使用一种基于最大熵模型确定评价因子权重的改进型栖息地适宜性指数模型,模拟了在约1米(5.3 - 14.2米)间隔的10个水位梯度下白鹤适宜栖息地的分布格局。结果表明,鄱阳湖淹没面积在过去20年总体呈缩减趋势,越冬初期滩涂出露面积显著增加(Z = -2.26)。由此导致的长期干旱将促使植被演替,从而减少白鹤在其自然栖息地的食物资源。6月的平均淹没面积与自然栖息地中白鹤种群数量呈显著负相关( = -0.75, = 0.02)。6月洪水导致白鹤偏好的[此处原文缺失具体植物名称]块茎短缺,是白鹤觅食策略改变和栖息地转移的主要驱动因素。在6月淹没情况相对正常、表明[此处原文缺失具体植物名称]资源丰富的年份,旱季淹没面积与白鹤种群数量之间的关系符合二次曲线( = 0.92, = 0.02)。旱季淹没面积主要通过影响食物资源的可利用性来影响白鹤种群数量和分布格局,淹没面积过大或过小都不利于白鹤生存。栖息地适宜性建模结果表明,随着水位下降,白鹤适宜栖息地面积的变化趋势呈倒钟形,在水位8.8米时达到峰值,最佳条件出现在8至10米之间。气候和人类活动的综合影响使得鄱阳湖食物资源短缺成为新常态。自然栖息地的退化导致白鹤栖息地质量下降,人工栖息地只能在一定程度上作为避难所。因此,制定恢复自然栖息地和加强人工栖息地管理的策略对于白鹤保护工作至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/47c251ead4fa/animals-14-00234-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/8588b2aff899/animals-14-00234-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/c21851932ced/animals-14-00234-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/575b5fa3c73f/animals-14-00234-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/b4443e000a48/animals-14-00234-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/ec8ac0626558/animals-14-00234-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/04d1280e45fd/animals-14-00234-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/47c251ead4fa/animals-14-00234-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/8588b2aff899/animals-14-00234-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/c21851932ced/animals-14-00234-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/575b5fa3c73f/animals-14-00234-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/b4443e000a48/animals-14-00234-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/ec8ac0626558/animals-14-00234-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/04d1280e45fd/animals-14-00234-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e99/10812764/47c251ead4fa/animals-14-00234-g007.jpg

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J Environ Manage. 2023 Sep 15;342:118157. doi: 10.1016/j.jenvman.2023.118157. Epub 2023 May 15.
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[Spatiotemporal distribution of in the southern Yellow Sea and East China Sea].
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