元群落模型和经验数据揭示了非对称网络约束鱼类扩散。

IF 3.7 1区 环境科学与生态学 Q1 ECOLOGY
Paul Savary
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引用次数: 0

摘要

Borthagaray, A. I, Teixeira de Mello, F.和Arim, M.(2025)。从鱼类生物多样性模式推断河流景观扩散过程。动物生态学杂志。https://doi.org/10.1111/1365 - 2656.70033。扩散是生物多样性的主要决定因素之一。已有研究指出,群落的多样性和组成不仅取决于群落的扩散速率,还取决于群落的扩散路径所形成的复杂空间网络。然而,超越这种观察来推断一个特定系统的空间明确的扩散网络仍然是一个挑战。Borthagaray等人(2025)将元群落模型和来自58个鱼类群落的经验数据结合起来,确定了内格罗河流域(乌拉圭)最有可能的扩散网络。他们评估了分散参数(源,(a)对称,距离衰减,势垒)的替代组合的经验支持。最佳支持组合表明,鱼类沿河流分支不对称分散;也就是说,下游的扩散比上游更强。然而,出口仍然是上游分散剂的重要来源,即使在很远的距离。虽然他们没有发现任何水坝屏障效应的证据,但这可能是由于对诱导破碎的滞后反应。通过充分利用元群落模型和经验数据,本研究展示了一种从经验数据推断复杂扩散模式的优雅方法,这种方法可以在其他系统中得到有利的复制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Metacommunity models and empirical data reveal asymmetric network-constrained fish dispersal

Metacommunity models and empirical data reveal asymmetric network-constrained fish dispersal

Metacommunity models and empirical data reveal asymmetric network-constrained fish dispersal

Metacommunity models and empirical data reveal asymmetric network-constrained fish dispersal

Metacommunity models and empirical data reveal asymmetric network-constrained fish dispersal

Borthagaray, A. I., Teixeira de Mello, F., & Arim, M. (2025). Inferring riverscape dispersal processes from fish biodiversity patterns. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.70033. Dispersal is one of the main determinants of biodiversity. Previous studies have pointed out that the diversity and composition of communities depend not only on dispersal rates, but also on the complex spatial networks formed by dispersal paths. However, going beyond this observation to infer a spatially explicit dispersal network for a particular system remains a challenge. Borthagaray et al. (2025) combined metacommunity models and empirical data from 58 fish communities to identify the most likely dispersal network in the large Negro River basin (Uruguay). They assessed the empirical support for alternative combinations of dispersal parameters (sources, (a)symmetry, distance decay, barriers). The best-supported combinations show that fish disperse asymmetrically along river branches; that is, dispersal is stronger downstream than upstream. Yet, the outlet remains an important source of upstream dispersers, even at large distances. Though they could not find evidence of any barrier effects of dams, this might be due to lagged responses to the induced fragmentation. By making the most of metacommunity models and empirical data, this study showcases an elegant way to infer complex dispersal patterns from empirical data, which could be advantageously replicated in other systems.

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来源期刊
Journal of Animal Ecology
Journal of Animal Ecology 环境科学-动物学
CiteScore
9.10
自引率
4.20%
发文量
188
审稿时长
3 months
期刊介绍: Journal of Animal Ecology publishes the best original research on all aspects of animal ecology, ranging from the molecular to the ecosystem level. These may be field, laboratory and theoretical studies utilising terrestrial, freshwater or marine systems.
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