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

University of Birmingham A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems Goddard, Mark A.; Davies, Zoe G.; Guenat, Solène; Ferguson, Mark J.; Fisher, Jessica C.; Akanni, Adeniran; Ahjokoski, Teija; Anderson, Pippin M.L.; Angeoletto, Fabio; Antoniou, Constantinos; Bates, Adam J.; Barkwith, Andrew; Berland, Adam; Bouch, Christopher J.; Rega-Brodsky, Christine C.; Byrne, Loren B.; Canavan, Rory; Chapman, Tim; Connop, Stuart; Crossland, Steve DOI: 10.1038/s41559-020-01358-z License: None: All rights reserved Document Version Peer reviewed version Citation for published version (Harvard): Goddard, MA, Davies, ZG, Guenat, S, Ferguson, MJ, Fisher, JC, Akanni, A, Ahjokoski, T, Anderson, PML, Angeoletto, F, Antoniou, C, Bates, AJ, Barkwith, A, Berland, A, Bouch, CJ, Rega-Brodsky, CC, Byrne, LB, Canavan, R, Chapman, T, Connop, S, Crossland, S, Dade, MC, Dawson, DA, Dobbs, C, Downs, CT, Ellis, EC, Escobedo, FJ, Gobster, P, Gulsrud, NM, Guneralp, B, Hahs, AK, Hale, JD, Hassall, C, Hedblom, M, Hochuli, DF, Inkinen, T, Ioja, IC, Kendal, D, Knowland, T, Kowarik, I, Langdale, SJ, Lerman, SB, MacGregor-Fors, I, Manning, P, Massini, P, McLean, S, Mkwambisi, DD, Ossola, A, Luque, GP, Pérez-Urrestarazu, L, Perini, K, Perry, G, Pett, TJ, Plummer, KE, Radji, RA, Roll, U, Potts, SG, Rumble, H, Sadler, JP, de Saille, S, Sautter, S, Scott, CE, Shwartz, A, Smith, T, Snep, RPH, Soulsbury, CD, Stanley, MC, Van de Voorde, T, Venn, SJ, Warren, PH, Washbourne, CL, Whitling, M, Williams, NSG, Yang, J, Yeshitela, K, Yocom, KP, Dallimer, M & Dave, C 2021, 'A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems', Nature Ecology and Evolution, vol. 5, no. 2, pp. 219-230. https://doi.org/10.1038/s41559-020-01358-z Link to publication on Research at Birmingham portal General rights Unless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. 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Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive. If you believe that this is the case for this document, please contact [email protected] providing details and we will remove access to the work immediately and investigate. Download date: 21. nov. 2023 1 A global horizon scan of the future impacts of robotics and autonomous 1 systems on urban ecosystems 2 3 Mark A. Goddard1,a, Zoe G. Davies2, Solène Guenat1, Mark J. Ferguson3, Jessica C. Fisher2, 4 Adeniran Akanni4, Teija Ahjokoski5, Pippin M.L. Anderson6, Fabio Angeoletto7, Constantinos 5 Antoniou8, Adam J. Bates9, Andrew Barkwith10, Adam Berland11, Christopher J. Bouch12, 6 Christine C. Rega-Brodsky13, Loren B. Byrne14, David Cameron15, Rory Canavan16, Tim 7 Chapman17, Stuart Connop18, Steve Crossland19, Marie C. Dade20, David A. Dawson21, 8 Cynnamon Dobbs22, Colleen T. Downs23, Erle C. Ellis24, Francisco J Escobedo25, Paul 9 Gobster26, Natalie Marie Gulsrud27, Burak Guneralp28, Amy K. Hahs28, James D. Hale30, 10 Christopher Hassall31, Marcus Hedblom32, Dieter F. Hochuli33, Tommi Inkinen34, Ioan-Cristian 11 Ioja35, Dave Kendal36, Tom Knowland37, Ingo Kowarik38, Simon J. Langdale39, Susannah B. 12 Lerman26, Ian MacGregor-Fors40, Peter Manning41, Peter Massini42, Stacey McLean43, David 13 D. Mkwambisi44, Alessandro Ossola45, Gabriel Pérez Luque46, Luis Pérez-Urrestarazu47, 14 Katia Perini48, Gad Perry49, Tristan J. Pett2, Kate E. Plummer50, Raoufou A. Radji51, Uri 15 Roll52, Simon G. Potts53, Heather Rumble54, Jon P. Sadler55, Stevienna de Saille56, 16 Sebastian Sautter57, Catherine E. Scott58, Assaf Shwartz59, Tracy Smith60, Robbert P.H. 17 Snep61, Carl D. Soulsbury62, Margaret C. Stanley63, Tim Van de Voorde64, Stephen J. 18 Venn65, Philip H. Warren66, Carla-Leanne Washbourne67, Mark Whitling68, Nicholas S.G. 19 Williams28, Jun Yang69, Kumelachew Yeshitela70, Ken P. Yocom71 and Martin Dallimer1* 20 21 1Sustainability Research Institute, School of Earth and Environment, University of Leeds, 22 Leeds, UK 23 2Durrell Institute of Conservation and Ecology (DICE), School of Anthropology and 24 Conservation, University of Kent, Canterbury, UK 25 3European Centre for Environment and Human Health, University of Exeter Medical School, 26 Knowledge Spa, Royal Cornwall Hospital, Truro, Cornwall, UK 27 4Lagos State Ministry of Environment, Lagos, Nigeria 28 5Bristol City Council, Bristol, UK 29 2 6Department of Environmental and Geographical Science, University of Cape Town, Cape 30 Town, South Africa 31 7Mestrado em Geografia da Universidade Federal de Mato Grosso, campus de 32 Rondonópolis, Rondonópolis, Brazil 33 8Department of Civil, Geo and Environmental Engineering, Technical University of Munich, 34 Munich, Germany 35 9School of Animal, Rural & Environmental Sciences, Nottingham Trent University, 36 Nottingham, UK 37 10British Geological Survey, Environmental Science Centre, Keyworth, Nottingham, UK 38 11Department of Geography, Ball State University, Muncie, Indiana, USA 39 12School of Engineering, University of Birmingham, Birmingham, UK 40 13Biology Department, Pittsburg State University, Pittsburg, Kansas, USA 41 14Department of Biology, Marine Biology and Environmental Science, Roger Williams 42 University, Bristol, Rhode Island, USA 43 15Information School, University of Sheffield, Sheffield, UK 44 16Arup Environmental, Arup, Rose Wharf, 78 East Street, Leeds, LS9 8EE, UK 45 17Infrastructure London Group, Arup, 13 Fitzroy Street, London, W1T 4BQ, UK 46 18Sustainability Research Institute, University of East London, London, UK 47 19Balfour Beatty, Thurnscoe Business Park, Barrowfield Road, Thurnscoe, S63 0BH, UK 48 20Department of Geography, McGill University, Montreal, Canada 49 21School of Civil Engineering, University of Leeds, Leeds, UK 50 22Facultad de Ciencias, Centro de Modelacion y Monitoreo de Ecosistemas, Universidad 51 Mayor, Santiago, Chile 52 23Centre for Functional Biodiversity, School of Life Sciences, University of KwaZulu-Natal, 53 Scottsville, Pietermaritzburg, South Africa 54 24Geography & Environmental Systems, University of Maryland, Baltimore, Maryland, USA 55 25Biology Department, Universidad del Rosario, Bogotá, Colombia 56 26USDA Forest Service Northern Research Station, Madison, Wisconsin, USA 57 27Department of Geosciences and Natural Resource Management, Section of Landscape 58 Architecture and Planning, University of Copenhagen, Copenhagen, Denmark 59 28Department of Geography, Texas A&M University, College Station, Texas, USA 60 29School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Australia 61 30Division of Conservation Biology, Institute of Ecology and Evolution, University of Bern, 62 Bern, Switzerland 63 31School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK 64 32Department of Urban and Rural Development, Swedish University of Agricultural Sciences, 65 Uppsala, Sweden 66 33School of Life and Environmental Sciences, University of Sydney, Sydney, Australia 67 3 34Brahea Centre, Centre for Maritime Studies, University of Turku, Turku, Finland 68 35Center for Environmental Research and Impact Studies, University of Bucharest, 69 Bucharest, Romania 70 36School of Technology, Environments and Design, University of Tasmania, Hobart, 71 Australia 72 37Leeds City Council, St George House, 40 Great George Street, Leeds, LS1 3DL, UK 73 38Institute of Plant Ecology, Technische Universität Berlin, Rothenburgstr, Berlin, Germany 74 39Synthotech Ltd, Hornbeam Park, Harrogate, UK 75 40Red de Ambiente y Sustentabilidad, Instituto de Ecología, A.C. (INECOL), Veracruz, 76 Mexico 77 41Senckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany 78 42Green Infrastructure, Greater London Authority, London, UK 79 43The Wildlife Land Fund, 30 Gladstone Road, Highgate Hill, Queensland 4101, Australia 80 44MUST Institute for Industrial Research and Innovation, Malawi University of Science and 81 Technology, Mikolongwe, Blantyre, Malawi 82 45Department of Plant Science, University of California, Davis, Callifornia, USA 83 46Department of Computer Science and Industrial Engineering, University of Lleida, Lleida, 84 Spain 85 47Urban Greening and Biosystems Engineering Research Group, Area of Agro-Forestry 86 Engineering, ETSIA, Universidad de Sevilla, Sevilla, Spain 87 48Architecture and Design Department, University of Genoa, Genoa, Italy 88 49Department of Natural Resource Management, Texas Tech University, Lubbock, Texas, 89 USA 90 50British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU, UK 91 51Laboratory of Forestry Research (LRF), University of Lomé, Lomé, Togo 92 52Mitrani Department of Desert Ecology, Jacob Blaustein Institutes for Desert Research, 93 Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel 94 53Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, 95 University of Reading, Reading, UK 96 54School of the Environment, Geography and Geosciences, University of Portsmouth, 97 Portsmouth, UK 98 55GEES (School of Geography, Earth and Environmental Sciences), University of 99 Birmingham, Birmingham, UK 100 56Institute for the Study of the Human (iHuman), Department of Sociological Studies, 101 University of Sheffield, Sheffield, UK 102 57SAUTTER ZT Advanced Energy Consulting, Graz, Austria 103 58Institute of Climate and Atmospheric Sciences, School of Earth and Environment, 104 University of Leeds, Leeds, UK 105 4 59Human and Biodiversity Research Lab, Faculty of Architecture and Town Planning, 106 Technion – Israel Institute of Technology, Haifa, Israel 107 60Amey Consulting, Precision House, McNeil Drive, Eurocentral, Motherwell, ML1 4UR 108 61Wageningen Environmental Research Wageningen University, Wageningen, The 109 Netherlands 110 62School of Life Sciences, University of Lincoln, Lincoln, UK 111 63School of Biological Sciences, University of Auckland, Auckland, New Zealand 112 64Department of Geography, Ghent University, Ghent, Belgium 113 65Ecosystems and Environment Research Programme, Faculty of Biological and 114 Environmental Sciences, University of Helsinki, Helsinki, Finland 115 66Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK 116 67Department of Science, Technology, Engineering and Public Policy, University College 117 London, London, UK 118 68Environment Agency, Foss House, Kings Pool, 1-2 Peasholme Green, York, YO1 7PX, UK 119 69Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth 120 System Science, Tsinghua University, Beijing, China 121 70Ecosystem Planning and Management, Ethiopian Institute of Architecture, Building 122 Construction and City Development (EiABC), Addis Ababa University, Addis Ababa, Ethiopia 123 71Department of Landscape Architecture, University of Washington, Seattle, Washington, 124 USA 125 126 * Corresponding author 127 a Current address: Department of Geography and Environmental Sciences, Northumbria 128 University, Newcastle upon Tyne, UK 129 130 5 Technology is transforming societies worldwide. A significant innovation is the 131 emergence of robotics and autonomous systems (RAS), which have the potential to 132 revolutionise cities for both people and nature. Nonetheless, the opportunities and 133 challenges associated with RAS for urban ecosystems have yet to be considered 134 systematically. Here, we report the findings of an online horizon scan involving 170 135 expert participants from 35 countries. We conclude that RAS are likely to transform 136 land-use, transport systems and human-nature interactions. The prioritised 137 opportunities were primarily centred on the deployment of RAS for monitoring and 138 management of biodiversity and ecosystems. Fewer challenges were prioritised. 139 Those that were emphasised concerns surrounding waste from unrecovered RAS, 140 and the quality and interpretation of RAS-collected data. Although the future impacts 141 of RAS for urban ecosystems are hard to predict, examining potentially important 142 developments early is essential if we are to avoid detrimental consequences, but fully 143 realise the benefits. 144 145 We are currently witnessing the fourth industrial revolution1. Technological innovations have 146 altered the way in which economies operate, and how people interact with built, social and 147 natural environments. One area of transformation is the emergence of robotics and 148 autonomous systems (RAS), defined as technologies that can sense, analyse, interact with 149 and manipulate their physical environment2. RAS include unmanned aerial vehicles 150 (drones), self-driving cars, robots able to repair infrastructure, and wireless sensor networks 151 used for monitoring. RAS therefore have a large range of potential applications, such as 152 autonomous transport, waste collection, infrastructure maintenance and repair, policing2,3, 153 and precision agriculture4 (Figure 1). RAS have already revolutionised how environmental 154 data are collected5, and species populations are monitored for conservation6 and/or control7. 155 Globally, the RAS market is projected to grow from $6.2 billion in 2018 to $17.7 billion in 156 20268. 157 6 158 Concurrent with this technological revolution, urbanisation continues at an unprecedented 159 rate. By 2030, an additional 1.2 million km2 of the planet’s surface will be covered by towns 160 and cities, with ~90% of this development happening in Africa and Asia. Indeed, 7 billion 161 people will live in urban areas by 20509. Urbanisation causes habitat loss, fragmentation and 162 degradation, as well as alters local climate, hydrology and biogeochemical cycles, resulting 163 in novel urban ecosystems with no natural analogs10. When poorly planned and executed, 164 urban expansion and densification can lead to substantial declines in many aspects of 165 human well-being11. 166 167 Presently, we have little appreciation of the pathways through which the widespread uptake 168 and deployment of RAS could affect urban biodiversity and ecosystems12,13. To date, 169 information on how RAS may impact urban biodiversity and ecosystems remains scattered 170 across multiple sources and disciplines, if it has been recorded at all. The widespread use of 171 RAS has been proposed as a mechanism to enhance urban sustainability14, but critics have 172 questioned this techno-centric vision15,16. Moreover, while RAS are likely to have far173 reaching social, ecological, and technological ramifications, these are often discussed only in 174 terms of the extent to which their deployment will improve efficiency and data harvesting, 175 and the associated social implications17-19. Such a narrow focus will likely overlook 176 interactions across the social-ecological-technical systems that cities are increasingly 177 thought to represent20. Without an understanding of the opportunities and challenges RAS 178 will bring, their uptake could cause conflict with the provision of high quality natural 179 environments within cities13, which can support important populations of many species21, and 180 are fundamental to the provision of ecosystem services that benefit people22. 181 182 7 Here we report the findings of an online horizon scan to evaluate and prioritise future 183 opportunities and challenges for urban biodiversity and ecosystems, including their structure, 184 function and service provision, associated with the emergence of RAS. Horizon scans are 185 not conducted to fill a knowledge gap in the conventional research sense, but are used to 186 explore arising trends and developments, with the intention of fostering innovation and 187 facilitating proactive responses by researchers, managers, policymakers and other 188 stakeholders23. Using a modified Delphi technique, which is a structured and iterative 189 survey23-25 (Figure 2), we systematically collated and synthesised knowledge from 170 190 expert participants based in 35 countries (Extended Data Fig. ). We designed the exercise to 191 involve a large range of participants and incorporate a diversity of perspectives26. 192 193 Results and Discussion 194 Following two rounds of online questionnaires, the participants identified 32 opportunities 195 and 38 challenges for urban biodiversity and ecosystems associated with RAS (Figure 2). 196 These were prioritised in Round Three, with participants scoring each opportunity and 197 challenge according to four criteria, using a 5-point Likert scale: (i) likelihood of occurrence; 198 (ii) potential impact (i.e. the magnitude of positive or negative effects); (iii) extensiveness (i.e. 199 how widespread the effects will be); and (iv) degree of novelty (i.e. how well known or 200 understood the issue is). Opportunities that highlighted how RAS could be used for 201 environmental monitoring scored particularly highly (Figure 3; Supplementary Table 1). In 202 contrast, fewer challenges received high scores. Those that did emphasised concerns 203 surrounding waste from unrecovered RAS, and the quality and interpretation of RAS204 collected data (Figure 4; Supplementary Table 1). 205 206 These patterns from the whole dataset masked heterogeneity between groups of 207 participants, which could be due to at least three factors: (i) variation in 208 8 background/expertise; (ii) variation in which opportunities and challenges are considered 209 important in particular contexts; and (iii) variation in experience and, therefore, perspectives. 210 We found variation according to participants’ country of employment and area of expertise 211 (Extended Data Fig. 2 and 3). However, we found no significant disagreement between 212 participants working in different employment sectors. This broad consensus suggests that 213 the priorities of the research community and practitioners are closely aligned. 214 215 Country of employment 216 Of our 170 participants, 11% were based in the Global South, suggesting that views from 217 that region might be under-represented. Nevertheless, this level of participation is broadly 218 aligned with the numbers of researchers working in different regions. For instance, urban 219 ecology is dominated by Global North researchers27,28. 220 221 There were significant divergences between the views of participants from the Global North 222 and South (Extended Data Fig. 4 and 5). Over two thirds (69%; n=44/64) of Global North 223 participants indicated that the challenge “Biodiversity will be reduced due to generic, 224 simplified and/or homogenised management by RAS” (item 11 in Supplementary Table 1) 225 would be important, assigning scores greater than zero. Global South participants expressed 226 much lower concern for this challenge, with only one participant assigning it a score above 227 zero (Fisher’s Exact Test: odds ratio=19.04 (95% CI 2.37–882.61), p=0.0007; Extended 228 Data Fig. 2). The discussions in Rounds Four and Five (Figure 2) revealed that participants 229 thought RAS management of urban habitats was not imminent in cities of the Global South, 230 due to a lack of financial, technical and political capacity. 231 232 15 across inaccessible or privately owned land. Ecoacoustic surveying and automated sampling 388 of environmental DNA (eDNA) is already enabling the monitoring of hard to detect 389 species83,84. RAS also offer potential to detect plant diseases in urban vegetation and, 390 subsequently inform control measures85,86. 391 392 Nevertheless, our participants highlighted that the technology and baseline taxonomy 393 necessary for the identification of the vast majority of species autonomously is currently 394 unavailable. If RAS cannot reliably monitor cryptic, little-known or unappealing taxa, the 395 existing trend for conservation actions to prioritise easy to identify and charismatic species in 396 well-studied regions could intensify87. Participants emphasised that easily collected RAS 397 data, such as tree canopy cover, could serve as surrogates for biodiversity and ecosystem 398 structure/function without proper evidence informing their efficacy. This would mirror current 399 practices, rather than offering any fundamental improvements in monitoring. Moreover, there 400 is a risk that subjective or intangible ecosystem elements (e.g. landscape, aesthetic, spiritual 401 benefits) that cannot be captured or quantified autonomously may be overlooked in decision402 making88. Participants expressed concern that the quantity, variety and complexity of big 403 data gathered by RAS monitoring could present new barriers to decision-makers when 404 coordinating citywide responses89. 405 406 Topic five: Managing invasive and pest species 407 The abundance and diversity of invasive and pest species are often high in cities90. One 408 priority concern identified by the participants is that RAS could facilitate new introduction 409 pathways, dispersal opportunities or different niches that could help invasive species to 410 establish. Participants noted that RAS offer clear opportunities for earlier and more efficient 411 pest and invasive species detection, monitoring and management91,92. However, participants 412 were concerned the implementation of such novel approaches, citing the potential for error, 413 16 whereby misidentification leads to accidentally controlling non-target species. Likewise, 414 RAS-mediated pest control could threaten unpopular taxa, such as wasps or termites, if the 415 interventions are not informed by knowledge of the important ecosystem functions such 416 species underpin. 417 418 Topic six: RAS interactions with animals 419 The negative impact of unmanned aerial vehicles on wildlife is well-documented93, but 420 evidence from some studies in non-urban settings suggest this impact may not be 421 universal94,95 . Nevertheless, participants highlighted that RAS activity at new heights and 422 locations within cities will generate novel threats, particularly for raptors that may perceive 423 drones as prey or competitors. Concentrating unmanned aerial vehicle activity along 424 corridors is a possible mitigation strategy. However, participants noted that this could further 425 fragment habitat by creating a 3-dimensional barrier to animal movement, which might 426 disproportionately affect migratory species. Similarly, ground-based or tree-climbing robots96 427 may disturb nesting and non-flying animals. 428 429 Topic seven: Managing pollution and waste 430 Air97,98, noise99 and light100,101 pollution can substantially alter urban ecosystem function. 431 Participants believed that RAS would generate a range of important opportunities for 432 reducing and mitigating such pollution. For instance, automated transport systems and road 433 repairs could reduce vehicle numbers and improve traffic flow36, leading to lower emissions 434 and improved air quality64,65. If increased autonomous vehicle use reduced noise from traffic, 435 species that rely on acoustic communication could benefit. Similarly, automated and 436 responsive lighting systems will reduce light impacts on nocturnal species, including 437 migrating birds102. RAS that monitor air quality, detect breaches of environmental law and 438 clean-up pollutants are already under development103,104. Waste management is a major 439 17 problem for urban sustainability, and participants noted that RAS105 could provide a solution 440 through automated detection and retrieval. Despite this potential, participants felt that 441 unrecovered RAS could themselves contribute to the generation of electronic waste, which is 442 a growing hazard for human, wildlife and ecosystem health106. 443 444 Topic eight: Water and flooding 445 Freshwater, estuarine, wetland and coastal habitats are valuable components of urban 446 ecosystems worldwide107. Maintenance of water, sanitation and wastewater infrastructure is 447 a major sustainability issue108. It is increasingly acknowledged that RAS could play a pivotal 448 role in how these systems are monitored and managed109, including improving drinking 449 water110, addressing water quality issues associated with sewerage systems111 and 450 monitoring and managing diverse aspects of stormwater predictions and flows112. 451 Participants therefore concluded that automated monitoring and management of water 452 infrastructure could lead to a reduction in pollution incidents, improve water quality and 453 reduce flooding113,114. Further, they felt that if stormwater flooding is diminished, there may 454 be scope for restoring heavily engineered river channels to a more natural condition, thereby 455 enhancing biodiversity, ecosystem function and service provision115. Participants identified, 456 however, that the opposite scenario could materialise, whereby RAS-maintained stormwater 457 infrastructure increases reliance on hard engineered solutions, decreasing uptake of nature458 based solutions (e.g. trees, wetlands, rain gardens, swales, retention basins) that provide 459 habitat and other ecosystem services116. 460 461 Conclusions 462 The fourth industrial revolution is transforming the way economies and society operate. 463 Identifying, understanding and responding to the novel impacts, both positive and negative, 464 18 of new technologies is essential to ensure that natural environments are managed 465 sustainably, and the provision of ecosystem services maximised. Here we identified and 466 prioritised the most important opportunities and challenges for urban biodiversity and 467 ecosystems associated with RAS. Such explicit consideration of how urban biodiversity and 468 ecosystems may be affected by the development of technological solutions in our towns and 469 cities is critical if we are to prevent environmental issues being sidelined. However, we have 470 to acknowledge that some trade-offs to the detriment of the environment are likely to be 471 inevitable. Additionally, it is highly probable that multiple RAS will be deployed 472 simultaneously, making it extremely difficult to anticipate interactive effects. To mitigate and 473 minimise any potential harmful effects of RAS, we recommend that environmental scientists 474 advocate for critical impact evaluations before phased implementation. Long-term 475 monitoring, comparative studies and controlled experiments could then further our 476 understanding of how biodiversity and ecosystems will be affected. This is essential as the 477 pace of technological change is rapid, challenging the capacity of environmental regulation 478 to respond quickly enough and appropriately. Although the future impacts of novel RAS are 479 hard to predict, early examination is essential to avoid detrimental and unintended 480 consequences on urban biodiversity and ecosystems, but fully realise the benefits. 481 19 Methods 482 Horizon scan participants 483 We adopted a mixed approach to recruiting experts to participant in the horizon scan to 484 minimise the likelihood of bias associated with relying on a single method. For instance, 485 snowball sampling (i.e. invitees suggesting additional experts who might be interested in 486 taking part) alone might over-represent individuals who are similar to one another, although 487 it can be effective at successfully recruiting individuals from hard-to-reach groups117. We 488 therefore contacted individuals directly via email inviting them to join the horizon scan, as 489 well as using social media and snowball sampling. The 480 experts working across the 490 research, private, public and NGO sectors globally contacted directly were identified through 491 professional networks, mailing lists (e.g. groups with a focus on urban ecosystems; the 492 research, development and manufacture of RAS; urban infrastructure), authors lists of 493 recently published papers, and via the editorial boards of subject-specific journals. Of the 494 170 participants who took part in Round One, 143 (84%) were individuals who has been 495 invited directly, with the remainder obtained through snowball sampling and social media. 496 497 We asked participants to indicate their area of expertise from five categories: (i) 498 environmental (including ecology, conservation and all environmental sciences); (ii) 499 infrastructure (including engineering and maintenance); (iii) sustainable cities (covering any 500 aspect of urban sustainability, including the implementation of ‘smart’ cities); (iv) RAS 501 (including research, manufacture and application); or (v) urban planning (including 502 architecture and landscape architecture). Participants whose area of expertise did not fall 503 within these categories were excluded from the process. We collected information on 504 participants’ country of employment. Subsequently, these were allocated into one of two 505 global regions, the Global North or Global South (low and middle income countries in South 506 America, Asia, Oceania, Africa, South America and the Caribbean118). Participants specified 507 20 their employment sector according to four categories: (i) research; (ii) government; (iii) 508 private business; or (iv) NGO/not-for-profit. 509 510 Participants were asked to provide informed consent prior to taking part in the horizon scan 511 activities. We made them aware that their involvement was entirely voluntary, that they could 512 stop at any point and withdraw from the process without explanation, and that their answers 513 would be anonymous and unidentifiable. Ethical approval was granted by the University of 514 Leeds Research Ethics Committee (reference LTSEE-077). We piloted and pre-tested each 515 round in the horizon scan process, which helped to refine the wording of questions and 516 definitions of terminology. 517 518 Horizon scan using the Delphi technique 519 The horizon scan applied a modified Delphi technique, which is applied widely in the 520 conservation and environmental sciences literature24. The Delphi technique is a structured 521 and iterative survey of a group of participants. It has a number of advantages over standard 522 approaches to gathering opinions from groups of people. For example, it minimises social 523 pressures such as groupthink, halo effects and the influence of dominant individuals24. The 524 first round can be largely unstructured, to capture a broad range and depth of contributions. 525 In our horizon scan, we asked each participant to identify between two and five ways in 526 which the emergence of RAS could affect urban biodiversity and/or ecosystem 527 structure/function via a questionnaire. They could either be opportunities (i.e. RAS would 528 have a positive impact on biodiversity and ecosystem structure/function) or challenges (i.e. 529 RAS would have a negative impact) (Figure 2). Round One resulted in the submission of 604 530 pertinent statements. We removed statements not relevant to urban biodiversity or urban 531 ecosystems. Likewise, we excluded statements relating to artificial intelligence or 532 virtual/augmented reality, as these technologies fall outside the remit of RAS. MAG 533 21 subsequently collated and categorised the statements into major topics through content 534 analysis. A total of sixty opportunities and challenges were identified. 535 536 In Round Two, we presented participants with the 60 opportunities and challenges, 537 categorised by topic, for review. We asked them to clarify, expand, alter or make additions 538 wherever they felt necessary (Figure 2). This round resulted in a further 468 statements and, 539 consequently, a further 10 opportunities and challenges emerged. 540 541 In Round Three, we used a questionnaire to ask participants to prioritise the 70 opportunities 542 and challenges in order of importance (Figure 2). We asked participants to score four 543 criteria25,119 using a 5-point Likert scale ranging from -2 (very low) to +2 (very high): (i) 544 likelihood of occurrence; (ii) potential impact (i.e. the magnitude of positive or negative 545 effects); (iii) extensiveness (i.e. how widespread the effects will be); and (iv) degree of 546 novelty (i.e. how well known or understood the issue is). A ‘do not know’ option was also 547 available. We randomly ordered the opportunities and challenges between participants to 548 minimise the influence of scoring fatigue120. For each participant, we generated a total score 549 (ranging from -8 to +8) for every opportunity and challenge by summing across all four 550 criteria. Opportunities and challenges were ranked according to the proportion of 551 respondents assigning them a summed score greater than zero. If a participant answered 552 ‘do not know’ for one or more of the criteria for a particular opportunity or challenge, we 553 excluded all their scores for that opportunity or challenge. We generated score visualisations 554 in the ‘Likert’ package121 of R version 3.4.1122. Two-tailed Fisher’s exact tests were used to 555 examine whether the percentage of participants scoring items above zero differed between 556 cohorts with different backgrounds (i.e. country of employment, employment sector and area 557 of expertise). 558 559 22 Final consensus on the most important opportunities and challenges was reached using 560 online group discussions (Round Four), followed by an online consensus workshop (Round 561 Five) (Figure 2; Supplementary Table 1). For Round Four, we allocated participants into one 562 of ten groups, with each group comprising of experts with diverse backgrounds. We asked 563 the groups to discuss the ranked 32 opportunities and 38 challenges, and agree on their ten 564 most important opportunities and ten most important challenges. It did not matter if these 565 differed from the Round Three rankings. Additionally, we asked groups to discuss whether 566 any of the opportunities or challenges were similar enough to be merged, and the 567 appropriateness, relevance and content of the topics. Across all groups, 14 opportunities 568 and 16 challenges were identified as most important. Participants, including at least one 569 representative from each of the ten discussion groups, took part in the consensus 570 workshop. The facilitated discussions resulted in agreement on the topics, and a final 571 consensus set of 13 opportunities and 15 challenges (Table 1). 572 573 Data Availability 574 Anonymised data are available from the University of Leeds institutional data repository at 575 https://doi.org/10.5518/912. 576 577 Acknowledgements 578 We are grateful to all our participants for taking part and to J. Bentley for preparing the 579 figures. The work was funded by the UK government’s Engineering and Physical Sciences 580 Research Council (grant EP/N010523/1: “Balancing the impact of City Infrastructure 581 Engineering on Natural systems using Robots”). ZGD was funded by the European 582 Research Council (ERC) under the European Union’s Horizon 2020 research and innovation 583 programme (Consolidator Grant No. 726104). 584 23 585 Author Contributions 586 MD conceived the study. MD, MAG, ZGD, SG, JCF, MJF developed and tested 587 questionnaire and webinar materials. All authors contributed data. MAG collated and 588 analysed these data. MAG, MD, ZGD led writing the paper, with all authors contributing and 589 agreeing to the final version. 590 591 24 Table 1. The most important 13 opportunities and 15 challenges associated with robotics and automated systems for urban biodiversity and ecosystems. The opportunities and challenges were prioritised as part of an online horizon scan involving 170 expert participants from 35 countries (Figure 2). The full set of 32 opportunities and 38 challenges identified by participants in Round Three is given in Supplementary Table 1. Item numbers given in parenthesis is for cross referencing between figures and tables. Topic Opportunities Challenges 1. Urban landuse and habitat availability Autonomous transport systems and associated decreased personal car ownership will reduce the amount of space needed for transport infrastructure (e.g. roads, car parks, driveways), allowing an increase in the extent and quality of urban green space and associated ecosystem services (item 54). The replacement of ecosystem services (e.g. air purification, pollination) by RAS (e.g. artificial 'trees', robotic pollinators) will lead to habitat and biodiversity loss (item 62). Trees and other habitat features will be reduced in extent or removed to facilitate easier RAS navigation, and/or damaged through direct collision (item 60). Autonomous transport systems will require new infrastructure (e.g. charging stations, maintenance and control facilities, vehicle depots), leading to the loss/fragmentation of greenspaces (item 59). 2. Maintenance and management of built and green infrastructure Smart buildings will be better able to regulate energy usage and reduce heat loss (e.g. through automated reflectors), reducing urban temperatures and providing less harsh microclimatic conditions for biodiversity under ongoing climate change (item 10). Biodiversity will be reduced due to generic, simplified and/or homogenised management by RAS. This includes over-intensive green space management, improved building maintenance and homogenisation of water currents and timings of flow (items 11, 14 and 37 merged). Irrigation of street trees and other vegetation by RAS will lead to greater resilience to climate change/urban heat stress (item 8). 31 Figure 4. Challenges associated with robotics and automated systems for urban biodiversity and ecosystems, ranked according to Round Three participant scores. The distribution of summed participant scores (range: -8 to +8) across four criteria (likelihood, impact, extent, novelty) for each of the 38 challenges. Items are ordered according to the percentage of participants who gave summed scores greater than zero. 32 Percentage values indicate the proportion of participants giving negative, neutral and positive scores (left hand side, central and right hand side of the shaded bars respectively). The full wording agreed by the participants for each challenge is in Supplementary Table 1: ‘mm’ is an abbreviation for ‘monitoring and management’; item number given in parenthesis is for cross-referencing between figures and tables. 33 References 1 Schwab, K. The Fourth Industrial Revolution. (Currency, 2017). 2 UK-RAS White Papers. Urban Robotics and Automation: Critical Challenges, International Experiments and Transferable Lessons for the UK. (2018). 3 Salvini, P. Urban robotics: Towards responsible innovations for our cities. 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