Coral reef restoration is an increasingly important part of tropical marine conservation. Information about what motivates coral reef restoration as well as its success and cost is not well understood but is needed to inform restoration decisions. We systematically review and synthesize data from mostly scientific studies published in peer‐reviewed and gray literature on the motivations for coral reef restoration, the variables measured, outcomes reported, the cost per hectare of the restoration project, the survival of restored corals, the duration of the project, and its overall spatial extent depending on the restoration technique employed. The main motivation to restore coral reefs for the projects assessed was to further our ecological knowledge and improve restoration techniques, with coral growth, productivity, and survival being the main variables measured. The median project cost was 400,000 US$/ha (2010 US$), ranging from 6,000 US$/ha for the nursery phase of coral gardening to 4,000,000 US$/ha for substrate addition to build an artificial reef. Restoration projects were mostly of short duration (1–2 years) and over small spatial extents (0.01 ha or 108 m2). Median reported survival of restored corals was 60.9%. Future research to survey practitioners who do not publish their discoveries would complement this work. Our findings and database provide critical data to inform future research in coral reef restoration.

Active restoration is becoming an increasingly important conservation intervention to counteract the degradation of marine coastal ecosystems. Understanding what has motivated the scientific community to research the restoration of marine coastal ecosystems and how restoration research projects are funded is essential if we want to scale-up restoration interventions to meaningful extents. Here, we systematically review and synthesize data to understand the motivations for research on the restoration of coral reefs, seagrass, mangroves, saltmarsh, and oyster reefs. We base this analysis off a published database of marine restoration studies, originally designed to estimate the cost and feasibility of marine coastal restoration, derived from mostly scientific studies published in peer-reviewed and some gray literature. For the present study, the database was updated with fields aimed at assessing the motivations, outcomes, and funding sources for each project. We classify restoration motivations into five categories: biotic, experimental, idealistic, legislative, and pragmatic. Moreover, we evaluate the variables measured and outcomes reported by the researchers and evaluate whether projects adhered to the Society for Ecological Restoration's (SER) standards for the practice of ecological restoration. The most common motivation of the scientific community to study restoration in marine coastal ecosystems was experimental i.e., to seek experimental data to answer ecological research questions or improve restoration approach, as expected since mostly peer-reviewed literature was evaluated here. There were differences in motivations among the five coastal ecosystems. For instance, biodiversity enhancement was the most common case for a biotic motivation in mangrove restoration projects. The most common metrics evaluated were growth/productivity, survivorship, habitat function, physical attributes, and reproduction. For most ecosystems, ecological outcomes were frequently reported, with socioeconomic implications of the restoration rarely mentioned, except for mangroves. Projects were largely funded by governmental Bayraktarov et al. Marine Restoration Motivations grants with some investment from private donations, non-governmental organizations, and the involvement of volunteers. Our findings and database provide critical data to align future research of the scientific community with the real social, economic and policy needs required to scale-up marine coastal restoration projects.

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Biodiversity offsets are a popular policy tool for mitigating the impact of development on biodiversity, but the ecological success of offsets arise from complex interactions among socio‐economic, ecological and policy processes, making outcomes challenging to assess. Many offset policies use habitat surrogates to determine offset requirements, rather than using direct measures of impacted biota, and this can lead to poor outcomes for species. One potential solution to this is for offsets to be delivered by a public agency (agency‐led) rather than by developers (developer‐led). This is because agencies may be able to strategically choose offset sites that maximise outcomes for species (e.g. abundance), while there may be little reason for developers to act strategically in this way when offset requirements are based purely on habitat surrogates. Yet, the success of a strategic agency‐led approach is likely to depend on patterns of development and offset site availability. To examine this, we developed a novel integrated spatially explicit model of land‐use change, habitat, species abundance and offset regulation. We apply the model to the Queensland Government's Environmental Offsets Policy for koalas Phascolarctos cinereus in South East Queensland, Australia, and test how patterns of development and offset site availability influence the performance of agency‐led versus developer‐led offsets. When potential offset sites were plentiful, agency‐led offsets tended to outperform developer‐led offset delivery for maximising koala abundance while achieving similar or better outcomes for habitat area. Yet, when potential offset sites were rare, the relative performance of agency‐led offset was often poor, and offset requirements for habitat area were less likely to be met. Different spatial patterns of development had little effect on the relative performance of agency‐led versus developer‐led offsets. Our analysis shows that agency‐led offsets with strategic choices of offset sites can improve species' outcomes for habitat‐based offsets but can also risk failing to meet habitat area requirements when the availability of offset sites is low. Importantly, our integrated spatial model provides a holistic approach to assessing policy options for biodiversity offsets in dynamic human‐modified landscapes. Read the free Plain Language Summary for this article on the Journal blog.