Abstract
Species composition and habitats are changing at unprecedented rates in the world's oceans, potentially causing entire food webs to shift to structurally and functionally different regimes. Despite the severity of these regime shifts, elucidating the precise nature of their underlying processes has remained difficult. We address this challenge with a new analytic approach to detect and assess the relative strength of different driving processes in food webs. Our study draws on complexity theory, and integrates the network-centric exponential random graph modelling (ERGM) framework developed within the social sciences with community ecology. In contrast to previous research, this approach makes clear assumptions of direction of causality and accommodates a dynamic perspective on the emergence of food webs. We apply our approach to analysing food webs of the Baltic Sea before and after a previously reported regime shift. Our results show that the dominant food web processes have remained largely the same, although we detect changes in their magnitudes. The results indicate that the reported regime shift may not be a system-wide shift, but instead involve a limited number of species. Our study emphasizes the importance of community-wide analysis on marine regime shifts and introduces a novel approach to examine food webs.
Highlights
Ever-increasing anthropogenic activities such as overfishing, invasive species transport, pollution and climate change can drive marine systems to suddenly shift to new regimes with often devastating effects for human communities relying on marine resources for their persistence [1]
Our analysis suggests that these different configurations, to a varying degree, are themselves driving the formation of the entire food web structures for both the coastal and open water areas, before and after the observed regime shift
This study presents a new analytic approach to reveal underlying processes in complex food webs and test whether they have changed or shifted significantly in the Baltic Sea due to increased anthropogenic activities
Summary
Ever-increasing anthropogenic activities such as overfishing, invasive species transport, pollution and climate change can drive marine systems to suddenly shift to new regimes (states) with often devastating effects for human communities relying on marine resources for their persistence [1]. Empirical research on marine regime shifts has proved to be difficult [2]. This gap can at least partly be ascribed to the analytically and empirically challenging task of trying to reveal underlying patterns and processes in large and complex datasets such as food webs (cf [3]). In practice, any large, abrupt and persistent change in any of the key state variables describing a system is often conceived as a regime shift [4]. The aim of this work is to show how complexity theory, in combination with a recently developed network modelling framework, can be used to disentangle the underlying interactions of species in system-wide food webs before and after a reported regime shift in the Baltic Sea
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