Effects of temperature on global patterns of tuna and billfish richness
Effects of temperature on global patterns of tuna and billfish richness
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DOI：
10.3354/meps07237
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发表时间：
2008-01-01
影响因子：
2.5
通讯作者：
Worm, Boris
中科院分区：
文献类型：
--
作者：
Boyce, Daniel G.;Tittensor, Derek P.;Worm, Boris
虽然金枪鱼和长嘴鱼具有重要的经济意义，并受到养护关注，但对全球多样性和分布格局的了解仍然很少。许多物种是高度洄游的，能够忍受广泛的温度范围。在本研究中，根据地理位置，从190个文献来源的18种金枪鱼和长嘴鱼的环境水温数据进行了合并。采用经验建模方法，将金枪鱼和长嘴鱼的温度耐受性与其全球多样性模式联系起来。计算每个种属在成虫和幼虫生命阶段的平均首选和耐受温度范围。平均耐受性数据，然后覆盖，以适应模型的金枪鱼和长嘴鱼的物种丰富度与环境水温。最佳拟合模型与网格化水温数据结合使用，以预测全球物种丰富度模式。根据水温数据预测的累积物种丰富度与观察到的延绳钓丰富度数据呈正相关（r = 0.577，p < 0.0001）。多样性始终在中纬度地区（10至35度N和S）的方式类似于其他远洋类群的高峰。这项分析提供了证据，表明金枪鱼和长嘴鱼的环境水温耐受性可用于预测全球范围内广泛的物种丰富度模式。
Although tunas and billfishes are of substantial economic importance and conservation concern, global patterns of diversity and distribution remain poorly understood. Many species are highly migratory and able to tolerate a wide thermal range. In the present study, ambient water temperature data for 18 species of tuna and billfish from 190 literature sources were combined according to geographical location. An empirical modelling approach was used to relate temperature tolerances of tunas and billfishes to their global diversity patterns. Mean preferred and tolerated temperature ranges were calculated for each species in the adult and juvenile life stages. Mean tolerance data were then overlaid in order to fit models relating the species richness of tunas and billfishes to ambient water temperature. The best-fit model was used in conjunction with gridded water temperature data to predict global species richness patterns. Cumulative species richness predictions from water temperature data were positively correlated with observed longline-derived richness data (r = 0.577, p < 0.0001). Diversity consistently peaked at intermediate latitudes (10 to 35 degrees N and S) in a manner similar to other pelagic taxa. This analysis provides evidence that the ambient water temperature tolerances of tunas and billfishes can be used to predict broad species richness patterns on a global scale.