AIM: Previous analyses of marine fish species richness based on presence‐absence data have shown changes with latitude and average species size, but little is known about the underlying processes. To elucidate these processes we use metabolic, neutral and descriptive statistical models to analyse how richness responds to maximum species length, fish abundance, temperature, primary production, depth, latitude and longitude, while accounting for differences in species catchability, sampling effort and mesh size. DATA: Results from 53,382 bottom trawl hauls representing 50 fish assemblages. LOCATION: The northern Atlantic from Nova Scotia to Guinea. TIME PERIOD: 1977–2013. METHODS: A descriptive generalized additive model was used to identify functional relationships between species richness and potential drivers, after which nonlinear estimation techniques were used to parameterize: (a) a ‘best’ fitting model of species richness built on the functional relationships, (b) an environmental model based on latitude, longitude and depth, and mechanistic models based on (c) metabolic and (d) neutral theory. RESULTS: In the ‘best’ model the number of species observed is a lognormal function of maximum species length. It increases significantly with temperature, primary production, sampling effort, and abundance, and declines with depth and, for small species, with the mesh size in the trawl. The ‘best’ model explains close to 90% of the deviance and the neutral, metabolic and environmental models 89%. In all four models, maximum species length and either temperature or latitude account for more than half of the deviance explained. MAIN CONCLUSIONS: The two mechanistic models explain the patterns in demersal fish species richness in the northern Atlantic almost equally well. A better understanding of the underlying drivers is likely to require development of dynamic mechanistic models of richness and size evolution, fit not only to extant distributions, but also to historical environmental conditions and to past speciation and extinction rates.

中文翻译：

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北大西洋鱼类的物种丰富度：模式隐藏的过程

目的：之前基于存在-不存在数据对海洋鱼类物种丰富度的分析表明，纬度和平均物种大小会发生变化，但对潜在过程知之甚少。为了阐明这些过程，我们使用代谢、中性和描述性统计模型来分析丰富度如何对最大物种长度、鱼类丰度、温度、初级生产、深度、纬度和经度做出反应，同时考虑物种可捕获性、采样工作和网格大小的差异. 数据：来自代表 50 种鱼群的 53,382 次底拖网捕捞的结果。位置：北大西洋从新斯科舍到几内亚。时间段：1977-2013。方法：使用描述性广义加性模型来确定物种丰富度和潜在驱动因素之间的功能关系，之后使用非线性估计技术参数化：(a) 基于功能关系的物种丰富度的“最佳”拟合模型，(b) 基于纬度、经度和深度的环境模型，以及基于 (c) 的机械模型代谢和（d）中性理论。结果：在“最佳”模型中，观察到的物种数量是最大物种长度的对数正态函数。它随着温度、初级生产力、采样工作量和丰度的增加而显着增加，并随着深度和对于小型物种的拖网网目尺寸而减少。“最佳”模型解释了接近 90% 的偏差，中性、代谢和环境模型解释了 89%。在所有四个模型中，最大物种长度和温度或纬度占解释的偏差的一半以上。主要结论：这两种机制模型几乎同样好地解释了北大西洋底层鱼类物种丰富度的模式。对潜在驱动因素的更好理解可能需要开发丰富度和大小演变的动态机制模型，不仅适合现存的分布，而且适合历史环境条件以及过去的物种形成和灭绝率。