School of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom; Aarhus University, Department of Ecoscience, Frederiksborgvej 399, PO Box 358, 4000 Roskilde, Denmark.
Lowestoft Laboratory, Centre for Environment, Fisheries and Aquaculture Science, NR33 0HT Lowestoft, United Kingdom.
Sci Total Environ. 2024 Nov 20;952:175762. doi: 10.1016/j.scitotenv.2024.175762. Epub 2024 Aug 26.
The success of non-native species (NNS) invasions depends on patterns of dispersal and connectivity, which underpin genetic diversity, population establishment and growth. In the marine environment, both global environmental change and increasing anthropogenic activity can alter hydrodynamic patterns, leading to significant inter-annual variability in dispersal pathways. Despite this, multi-generational dispersal is rarely explicitly considered in attempts to understand NNS spread or in the design of management interventions. Here, we present a novel approach to quantifying species spread that considers range expansion and network formation across time using the non-native Pacific oyster, Magallana gigas (Thunberg 1793), as a model. We combined biophysical modelling, dynamic patch occupancy models, consideration of environmental factors, and graph network theory to model multi-generational dispersal in northwest Europe over 13 generations. Results revealed that M. gigas has a capacity for rapid range expansion through the creation of an ecological network of dispersal pathways that remains stable through time. Maximum network size was achieved in four generations, after which connectivity patterns remained temporally stable. Multi-generational connectivity could therefore be divided into two periods: network growth (2000-2003) and network stability (2004-2012). Our study is the first to examine how dispersal trajectories affect the temporal stability of ecological networks across biogeographic scales, and provides an approach for the assignment of site-based prioritisation of non-native species management at different stages of the invasion timeline. More broadly, the framework we present can be applied to other fields (e.g. Marine Protected Area design, management of threatened species and species range expansion due to climate change) as a means of characterising and defining ecological network structure, functioning and stability.
非本地物种（NNS）入侵的成功取决于扩散和连通性模式，这些模式是遗传多样性、种群建立和增长的基础。在海洋环境中，全球环境变化和人类活动的增加都会改变水动力模式，导致扩散途径的年际变化显著。尽管如此，在试图理解 NNS 传播或设计管理干预措施时，很少明确考虑多代扩散。在这里，我们提出了一种新的方法来量化物种传播，该方法考虑了使用非本地太平洋牡蛎 Magallana gigas（Thunberg 1793）作为模型的范围扩展和网络形成随时间的变化。我们结合了生物物理建模、动态斑块占据模型、环境因素的考虑以及图网络理论，来模拟西北欧超过 13 代的多代扩散。结果表明，M. gigas 具有通过创建扩散途径的生态网络快速扩展范围的能力，该网络随时间保持稳定。最大网络规模在四代后达到，之后连接模式保持时间稳定。因此，多代连接性可以分为两个时期：网络增长（2000-2003 年）和网络稳定（2004-2012 年）。我们的研究首次检验了扩散轨迹如何影响跨生物地理尺度的生态网络的时间稳定性，并提供了一种方法，可用于在入侵时间线上的不同阶段为非本地物种管理分配基于地点的优先事项。更广泛地说，我们提出的框架可以应用于其他领域（例如海洋保护区设计、受威胁物种管理和气候变化导致的物种范围扩展），作为描述和定义生态网络结构、功能和稳定性的一种手段。
