We propose that the coral holobiont should be conceptualized as a diverse transient microbial community that is responsive to the surrounding environment and encompasses a simple, redundant, resident microbiome and a small conserved core microbiome. Most importantly, we show that the coral microbiome is comparable to the microbiomes of other organisms studied thus far. Accurately characterizing the coral-microbe interactions provides an important baseline from which the functional roles and the functional niches within which microbes reside can be deciphered.

Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org). There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs); however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample) was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST) and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index) were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution), we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses.

Camera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012–2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in‐person workshop of 28 leading experts representing academia, non‐governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources. We predicted that the last decade would have shown: (i) exponentially increasing sampling effort, a continuation of camera usage trends up to 2012; (ii) analytics to have shifted from naive presence/absence and capture rates towards hierarchical modelling that accounts for imperfect detection, thereby improving the quality of outputs and inferences on occupancy, abundance, and density; and (iii) broader research scales in terms of multi‐species, multi‐site and multi‐year studies. However, the results showed that the sampling effort has reached a plateau, with publication rates increasing only modestly. Users reported reaching a saturation point in terms of images that could be processed by humans and time for complex analyses and academic writing. There were strong taxonomic and geographic biases towards medium–large mammals (>500 g) in forests along Australia's southeastern coastlines, reflecting proximity to major cities. Regarding analytical choices, bias‐prone indices still accounted for ~50% of outputs and this was consistent across user groups. Multi‐species, multi‐site and multiple‐year studies were rare, largely driven by hesitancy around collaboration and data sharing. There is no widely used repository for wildlife camera images and the Atlas of Living Australia (ALA) is the dominant repository for sharing tabular occurrence records. However, the ALA is presence‐only and thus is unsuitable for creating detection histories with absences, inhibiting hierarchical modelling. Workshop discussions identified a pressing need for collaboration to enhance the efficiency, quality and scale of research and management outcomes, leading to the proposal of a Wildlife Observatory of Australia (WildObs). To encourage data standards and sharing, WildObs should (i) promote a metadata collection app; (ii) create a tagged image repository to facilitate artificial intelligence/machine learning (AI/ML) computer vision research in this space; (iii) address the image identification bottleneck via the use of AI/ML‐powered image‐processing platforms; (iv) create data commons for detection histories that are suitable for hierarchical modelling; and (v) provide capacity building and tools for hierarchical modelling. Our review highlights that while Australia's investments in monitoring biodiversity with cameras position it to be a global leader in this context, realising that potential requires a paradigm shift towards best practices for collecting, curating, sharing and analysing ‘Big Data’. Our findings and framework have broad applicability outside Australia to enhance camera usage to meet conservation and management objectives ranging from local to global scales. This review articulates a country/continental observatory approach that is also suitable for international collaborative wildlife research networks.

Shellfish reefs across the world have been heavily degraded by mechanical harvesting, disease and declining water quality. In southern Australia, where substantial losses have occurred, government and non‐government efforts to restore functioning reefs are now underway with a strong focus on enhancing fish productivity. However, the capacity of these restored reefs to enhance fish production remains unknown, hampering estimates of return on investment. We quantify the density differences of newly recruited juvenile fish and other nekton on these restored reefs, relative to those on unrestored, unstructured habitat. Fish were surveyed at three paired reef‐unstructured locations using 169 unbaited stereo video deployments during three periods over 12 months (2022–2023). We used automation software, FishID, to automatically identify, size and count fish in videos. We subsequently applied known growth and mortality parameters to model enhancement of fish productivity. Sixteen species occurred as new recruits, with all but two found at higher densities on reefs than unstructured habitat. Enhancement of fish production from subtidal restored shellfish reefs from a single year's cohort is estimated to be, on average, 6186 kg ha⁻¹ year⁻¹ (SD 1802) after enough time has elapsed for all species to have matured. Species harvested commercially or recreationally contributed 98% of that production (6083 kg ha⁻¹ year⁻¹, SD 1797). Enhancement varied greatly among locations, ranging from 12,738 kg ha⁻¹ year⁻¹ (SD 2894), which is the highest yet recorded anywhere, to 1.4 kg ha⁻¹ year⁻¹ (SD 0.9). The lack of juvenile fish at the location with the lowest estimated enhancement might be explained by the impact of overfishing on recruitment of key species or by an abundance of alternative habitat for juvenile fish. Synthesis and applications. The combination of underwater videos with automated data extraction provides a reliable, cost‐effective method for surveying fish on oyster reefs. By quantifying enhanced fish productivity on reefs, we provide estimates that will underpin calculations of ecological, social and financial benefits, supporting the business case for scaling‐up restoration efforts.