A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems.

Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human-nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits.

Renewable energy production will exacerbate mining threats to biodiversity.

Renewable energy production is necessary to halt climate change and reverse associated biodiversity losses. However, generating the required technologies and infrastructure will drive an increase in the production of many metals, creating new mining threats for biodiversity. Here, we map mining areas and assess their spatial coincidence with biodiversity conservation sites and priorities. Mining potentially influences 50 million km2 of Earth's land surface, with 8% coinciding with Protected Areas, 7% with Key Biodiversity Areas, and 16% with Remaining Wilderness. Most mining areas (82%) target materials needed for renewable energy production, and areas that overlap with Protected Areas and Remaining Wilderness contain a greater density of mines (our indicator of threat severity) compared to the overlapping mining areas that target other materials. Mining threats to biodiversity will increase as more mines target materials for renewable energy production and, without strategic planning, these new threats to biodiversity may surpass those averted by climate change mitigation.

Advancing Systematic Conservation Planning for Ecosystem Services.

Conservation and sustainable management activities are critical for enhancing ecosystem services. Systematic conservation planning (SCP) is a spatial decision support process used to identify the most cost-effective places for intervention and is increasingly incorporating ecosystem services thinking. Yet, there is no clear guidance on how to incorporate ecosystem service components (i.e., supply, demand, and flow) for multiple beneficiaries into the decision problem underpinning SCP. As such, conservation plans may fall short of maximizing benefits for both people and nature. We propose a benefit-based approach to integrate ecosystem service components into SCP that uses the principles of decision theory. Our approach will improve the likelihood that ecosystem service benefits are enhanced in spatial planning applications.

Assessing ecosystem service trade-offs and synergies: The need for a more mechanistic approach.

Positive (synergistic) and negative (trade-off) relationships among ecosystem services are influenced by drivers of change, such as policy interventions and environmental variability, and the mechanisms that link these drivers to ecosystem service outcomes. Failure to account for these drivers and mechanisms can result in poorly informed management decisions and reduced ecosystem service provision. Here, we review the literature to determine the extent to which drivers and mechanisms are considered in assessments of ecosystem service relationships. We show that only 19% of assessments explicitly identify the drivers and mechanisms that lead to ecosystem service relationships. While the proportion of assessments considering drivers has increased over time, most of these studies only implicitly consider the drivers of ecosystem service relationships. We recommend more assessments explicitly identify drivers of trade-offs and synergies, which can be achieved through a greater uptake of causal inference and process-based models, to ensure effective management of ecosystem services.