Centre de Bretagne, DYNECO, Laboratoire d'Ecologie Benthique Côtière (LEBCO), IFREMER, Plouzané, France.
Laboratoire Évolution & Diversité Biologique (EDB), CNRS, Université de Toulouse, Toulouse, France.
PeerJ. 2022 Feb 23;10:e12857. doi: 10.7717/peerj.12857. eCollection 2022.
Population dynamics are driven by a number of biotic (, density-dependence) and abiotic (, climate) factors whose contribution can greatly vary across study systems (, populations). Yet, the extent to which the contribution of these factors varies across populations and between species and whether spatial patterns can be identified has received little attention.
Here, we used a long-term (1982-2011), broad scale (182 sites distributed across metropolitan France) dataset to study spatial patterns in the population's dynamics of three freshwater fish species presenting contrasted life-histories and patterns of elevation range shifts in recent decades. We used a hierarchical Bayesian approach together with an elasticity analysis to estimate the relative contribution of a set of biotic (, strength of density dependence, recruitment rate) and abiotic (mean and variability of water temperature) factors affecting the site-specific dynamic of two different size classes (0 and >0 individuals) for the three species. We then tested whether the local contribution of each factor presented evidence for biogeographical patterns by confronting two non-mutually exclusive hypotheses: the "range-shift" hypothesis that predicts a gradient along elevation or latitude and the "abundant-center" hypothesis that predicts a gradient from the center to the edge of the species' distributional range.
Despite contrasted life-histories, the three species displayed similar large-scale patterns in population dynamics with a much stronger contribution of biotic factors over abiotic ones. Yet, the contribution of the different factors strongly varied within distributional ranges and followed distinct spatial patterns. Indeed, while abiotic factors mostly varied along elevation, biotic factors-which disproportionately contributed to population dynamics-varied along both elevation and latitude.
Overall while our results provide stronger support for the range-shift hypothesis, they also highlight the dual effect of distinct factors on spatial patterns in population dynamics and can explain the overall difficulty to find general evidence for geographic gradients in natural populations. We propose that considering the separate contribution of the factors affecting population dynamics could help better understand the drivers of abundance-distribution patterns.
种群动态受多种生物因素（如密度依赖性）和非生物因素（如气候）驱动，这些因素的贡献在不同的研究系统（种群）中可能有很大差异。然而，这些因素在不同种群和物种之间的贡献程度以及是否可以识别空间模式的问题，尚未得到足够的关注。
在这里，我们使用了一个长期的（1982-2011 年）、广泛的（182 个分布在法国大都市地区的地点）数据集，研究了三种淡水鱼类种群动态的空间模式，这些鱼类具有不同的生活史和近几十年来海拔范围转移模式。我们使用了分层贝叶斯方法和弹性分析，来估计一组生物因素（如密度依赖性强度、繁殖率）和非生物因素（水温的平均值和变异性）对三个不同大小类别的特定地点动态的相对贡献（0 和>0 个体）。然后，我们通过对比两个非相互排斥的假设来检验每个因素的局部贡献是否存在生物地理模式：“范围转移”假设预测沿海拔或纬度的梯度，“丰富中心”假设预测从物种分布范围的中心到边缘的梯度。
尽管生活史不同，但这三种鱼类的种群动态表现出相似的大尺度模式，生物因素的贡献明显大于非生物因素。然而，不同因素的贡献在分布范围内有很大的变化，并呈现出不同的空间模式。事实上，虽然非生物因素主要沿海拔变化，但对种群动态有不成比例贡献的生物因素沿海拔和纬度变化。
总的来说，虽然我们的结果为范围转移假设提供了更强的支持，但它们也突出了不同因素对种群动态空间模式的双重影响，并解释了为什么在自然种群中很难找到一般的地理梯度证据。我们提出，考虑影响种群动态的因素的单独贡献，可以帮助更好地理解丰度分布模式的驱动因素。
