Mechatronic devices installed as Ecosystem Management and Monitoring Units, EMUs, are an emerging trend with the potential to improve our understanding of natural and agricultural ecosystems. They may improve biodiversity and provide socio-economic benefits, but if poorly implemented such technology can undermine conservation efforts, damage habitat and drive people into poverty. This article proposes draft guidelines that help to ensure EMUs embedded within ecosystems generate more global benefit than harm, preserve the aesthetic and cultural value of their environment, and kill organisms only as a last resort.

The influence of Artificial Intelligence (AI) and Artificial Life (ALife) technologies upon society, and their potential to fundamentally shape the future evolution of humankind, are topics very much at the forefront of current scientific, governmental and public debate. While these might seem like very modern concerns, they have a long history that is often disregarded in contemporary discourse. Insofar as current debates do acknowledge the history of these ideas, they rarely look back further than the origin of the modern digital computer age in the 1940s–50s. In this paper we explore the earlier history of these concepts. We focus in particular on the idea of self-reproducing and evolving machines, and potential implications for our own species. We show that discussion of these topics arose in the 1860s, within a decade of the publication of Darwin’s The Origin of Species , and attracted increasing interest from scientists, novelists and the general public in the early 1900s. After introducing the relevant work from this period, we categorise the various visions presented by these authors of the future implications of evolving machines for humanity. We suggest that current debates on the co-evolution of society and technology can be enriched by a proper appreciation of the long history of the ideas involved.

This paper presents a novel application of agent-based simulation software to tune real greenhouse infrastructure containing flowering seed or vegetable crop plants and their insect pollinators. Greenhouses provide controlled environments for the growth of high-value crops. As global climate and weather become more unpredictable, we are becoming more dependent upon technologically sophisticated greenhouses for reliable crop production. For crop pollination in a greenhouse, although manual or technological alternatives have been explored, pollination by bees is still required in many crops for the best seed yields and food quality. However, the design of greenhouses is driven primarily by the requirements of the plants rather than the pollinators. In light of this, we have designed simulations to explore improvements to greenhouse conditions and layout that benefit the insect pollinators and assist them to pollinate the crop. The software consists of an agent-based model of insect behaviour that is used to predict pollination outcomes under a range of conditions. The best parameters discovered in simulation can be used to adjust real greenhouse layouts. We present a key test case for our method, and discuss future work in which the technique has the potential to be applied in a continuous feedback loop providing predictions of greenhouse re-configurations that can be made by real-time control systems in a modern greenhouse. This is a novel approach linking simulation behaviour to real techno-ecological systems to improve crop and seed yield from valuable greenhouse infrastructure.