美国科学家的最新研究显示，随着加勒比海地区人口数量增加，生活在加勒比海域珊瑚礁水域的鲨鱼、梭鱼和其他大型鱼类正在消失，从而威胁该区域的海洋食物链和生物多样性，并可能最终危及珊瑚礁自身以及地区渔业。
据新一期的美国《公共图书馆·综合》杂志报道，在加勒比海海域从事研究的科学家近几十年来不断报告说，该海域大型鱼类数量不断下降。美国俄勒冈州立大学海岸和海洋实验室科学家斯托林斯等人对加勒比海地区的20种大型鱼类进行了研究，证明人类活动造成珊瑚礁水域大型鱼类数量下降。
斯托林斯说：“我发现拥有珊瑚礁的国家中，如果人口较多，则当地海域大型鱼类数量较少。因为随着人口数量的上升，他们对海产品的需求量也随之上升。渔民通常情况下先捕捞大型鱼类，当大鱼被捕尽时就会转而捕捞较小的鱼类，从而逐渐威胁到整个渔业资源的稳定。”
在全球海洋中，珊瑚礁所占面积不足0．25％，而有超过四分之一的已知海洋鱼类是靠珊瑚礁生活的，二者相互依存。坚硬的珊瑚礁可保护陆地和岛屿免遭海浪侵蚀，被认为是地球上最古老、最多姿多彩、也是最珍贵的生态系统之一。
斯托林斯认为，由于世界近一半人口生活在沿海区域，随着世界总人口的不断攀升，人类对海产蛋白质的需求也会不断增加。他认为，要想在满足这些需求的同时保护珊瑚礁及珊瑚礁水域鱼类，人们必须制订新的海洋渔业规划。（生物谷Bioon.com）
生物谷推荐原始出处：
PLoS ONE 4(5): e5333. doi:10.1371/journal.pone.0005333
Fishery-Independent Data Reveal Negative Effect of Human Population Density on Caribbean Predatory Fish Communities
Christopher D. Stallings
Department of Zoology, Oregon State University, Corvallis, Oregon, United States of America
Background
Understanding the current status of predatory fish communities, and the effects fishing has on them, is vitally important information for management. However, data are often insufficient at region-wide scales to assess the effects of extraction in coral reef ecosystems of developing nations.
Methodology/Principal Findings
Here, I overcome this difficulty by using a publicly accessible, fisheries-independent database to provide a broad scale, comprehensive analysis of human impacts on predatory reef fish communities across the greater Caribbean region. Specifically, this study analyzed presence and diversity of predatory reef fishes over a gradient of human population density. Across the region, as human population density increases, presence of large-bodied fishes declines, and fish communities become dominated by a few smaller-bodied species.
Conclusions/Significance
Complete disappearance of several large-bodied fishes indicates ecological and local extinctions have occurred in some densely populated areas. These findings fill a fundamentally important gap in our knowledge of the ecosystem effects of artisanal fisheries in developing nations, and provide support for multiple approaches to data collection where they are commonly unavailable.
