Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

Knowledge Transfer in Quadruple Helix Ecosystems: An Absorptive Capacity Perspective

Increased understanding of knowledge transfer (KT) from universities to the wider regional knowledge ecosystem offers opportunities for increased regional innovation and commercialisation. The aim of this article is to improve the understanding of the KT phenomena in an open innovation context where multiple diverse quadruple helix stakeholders are interacting. An absorptive capacity-based conceptual framework is proposed, using a priori constructs which portrays the multidimensional process of KT between universities and its constituent stakeholders in pursuit of open innovation and commercialisation. Given the lack of overarching theory in the field, an exploratory, inductive theory building methodology was adopted using semi-structured interviews, document analysis and longitudinal observation data over a three-year period. The findings identify five factors, namely human centric factors, organisational factors, knowledge characteristics, power relationships and network characteristics, which mediate both the ability of stakeholders to engage in KT and the effectiveness of knowledge acquisition, assimilation, transformation and exploitation. This research has implications for policy makers and practitioners by identifying the need to implement interventions to overcome the barriers to KT effectiveness between regional quadruple helix stakeholders within an open innovation ecosystem.

Metabolism of mineral-sorbed organic matter depends upon microbial lifestyle in fluvial ecosystems

In fluvial ecosystems mineral erosion, carbon (C) and nitrogen (N) fluxes are linked via organo-mineral complexation, where dissolved organic molecules bind to mineral surfaces. Biofilms and suspended aggregates represent major aquatic microbial lifestyles whose relative importance changes predictably through fluvial networks. We tested how organo-mineral sorption affects aquatic microbial metabolism, using organo-mineral particles containing a mix of ¹³C, ¹⁵N-labelled amino acids. We traced ¹³C and ¹⁵N retention within biofilm and suspended aggregate biomass and its mineralisation. Organo-mineral complexation restricted C and N retention within biofilms and aggregates and also their mineralisation. This reduced the efficiency with which biofilms mineralise C and N by 30 % and 6 %. By contrast, organo-minerals reduced the C and N mineralisation efficiency of suspended aggregates by 41 % and 93 %. Our findings show how organo-mineral complexation affects microbial C:N stoichiometry, potentially altering the biogeochemical fate of C and N within fluvial ecosystems.

Aquatic noise pollution: implications for individuals, populations, and ecosystems

Anthropogenically driven environmental changes affect our planet at an unprecedented scale, and are considered to be a key threat to biodiversity. According to the World Health Organisation, anthropogenic noise is one of the most hazardous forms of anthropogenically driven environmental change and is recognised as a major global pollutant. However, crucial advances in the rapidly emerging research on noise pollution focus exclusively on single aspects of noise pollution, e.g. on behaviour, physiology, terrestrial ecosystems or by focusing on certain taxa. Given that more than two thirds of our planet is covered with water, there is a pressing need to get a holistic understanding of the effects of anthropogenic noise in aquatic ecosystems. We found experimental evidence for negative effects of anthropogenic noise on an individual’s development, physiology, and/or behaviour in both invertebrates and vertebrates. We also found that species differ in their response to noise, and highlight the potential underlying mechanisms for these differences. Finally, we point out challenges in the study of aquatic noise pollution and provide directions for future research, which will enhance our understanding of this globally present pollutant.