Viviana Brambilla

Ecosystem engineers are ecological niche constructors: by modifying local environments, they alter the conditions under which organisms establish, persist and interact. Although niche construction is often framed as a population-level evolutionary feedback, it could also operate at the assemblage level when communities collectively shape their environments and filter future recruitment. Reef-building corals provide a perfect system to test this idea because adult colonies form three-dimensional carbonate structures that can persist after colony death, creating an inherited habitat for subsequent coral generations. Here, we tested whether coral recruitment to the juvenile stage was associated with local adult coral abundance, reef structure, and larval settlement supply. Combining spatially explicit coral censuses, photogrammetric reef digital elevation models and data from settlement tiles across 15 reef sites at two time points at Jiigurru, Great Barrier Reef, we found that juvenile abundance increased additively on the log scale with adult abundance and with fractal dimension, a metric of fine-scale structural complexity. Surface rugosity had weaker effects, and interactions between adult abundance and habitat structure were limited, indicating largely additive, rather than synergistic or antagonistic, effects. Our results show that both adult assemblages and the concurrent structural complexity, consistent with assemblage-level niche construction and ecological inheritance theory, shape coral recruitment.

The spatial distribution of environmental conditions fundamentally determines where organisms can and cannot live. When the distribution of micro‐environments within a landscape is mediated by the shape of its surface, structural complexity can indirectly affect environmental niche distributions. This study investigates how light availability patterns, particularly Photosynthetically Active Radiation (PAR), change along a gradient of habitat complexities measured as surface rugosity and height range in tropical shallow reefs. We used 903 high spatial resolution light measurements across different locations (mean minimum pairwise distance within site = 0.49 m) to determine the proportion of incoming light that is available at the reef surface. After accounting for light attenuation due to depth, light availability decreased with increasing surface rugosity: a unit increase in local surface rugosity corresponds to an 11–29% decrease in light availability. Nonetheless, we found that light availability on the reef surface is highly variable even at low complexity sites, with proximate locations experiencing up to 86.7% difference in daily photon input (25.7 mol/m ² /d). Local surface complexity affects distributions of light availability, while site‐scale metrics do not capture this variability. While decreasing overall light availability and potential photosynthetic activity, structural complexity enhances environmental variability, and so it is essential for understanding ecosystem functioning and its processes.

Remote underwater video (RUV) surveys are increasingly replacing diver‐based underwater visual censuses (UVCs) in fish ecology studies, especially on coral reefs. However, extracting reliable estimates of abundance or density from video footage is a major challenge, with most studies using a metric of relative abundance, MaxN (maximum number of concurrent conspecific individuals). Here we compare a video survey density estimation method used in terrestrial wildlife management, random encounter staying time modelling (REST) to MaxN from unbaited videos and density estimates from diver‐based UVC. We assess and compare the three approaches according to labour intensiveness (survey time effort per m ² ), species detection, abundance estimates and potential biases against size or aggregation behaviour. We found that species detection in REST was highly sensitive to sampling effort due to the minimum number of detections required for model fitting. There was also considerable variation in REST‐estimated absolute densities between species compared with other methods, however, each method was able to detect compositional differences among sites. While UVC was far less labour intensive than REST or MaxN in survey and processing effort, species richness was consistently lower in UVC observations compared to that from the two video‐based approaches. Pairwise generalised linear mixed models between method abundances showed that UVC abundances tended to be higher than other methods for shoaling/schooling fish. Our study identified strengths and weaknesses in each method for specific research objectives that may prioritise species detections or precision in abundance estimates. Although labour intensive, we found REST a viable alternative to MaxN if absolute abundance estimates are preferred. If precise abundance estimates are not a priority and labour is limited, we found MaxN suitable for capturing species richness. Finally, UVC ranked best in labour effectiveness in terms of both person‐hours and spatial coverage, and it provided good estimates of abundance, but generally lower species richness. Ultimately, method selection depends on study‐specific priorities and trade‐offs.

The shape of reef-building corals largely determines how they interact with their environment and the ecosystem services they provide. However, morphology is not fixed. As corals grow and develop from singular polyps to mature adult colonies, they experience pronounced changes in their morphology. This developmental trait variation remains poorly quantified in corals, despite their importance as ecosystem engineers. To address this gap, we used photogrammetry to track the morphological development of wild coral colonies across six size-independent metrics designed to capture variation in volume compactness, surface complexity, and top-heaviness. Size-trait models and analyses of colony movement through morphological trait space revealed that small colonies shared compact morphologies and only later diverged along growth-form-specific developmental trajectories. Massive corals largely retained stable shapes as they grew, whereas non-massive colonies became less compact, more top-heavy, and in most cases, more complex. Despite these differences, there was still overlap between growth forms in their developmental trajectories through morphospace. These findings highlight that traditional categorical growth forms mask important developmental variation, particularly early in coral ontogeny. By applying a quantitative trait-based framework, this study improves understanding of coral morphological development and provides a foundation for linking individual growth trajectories to broader reef ecosystem dynamics.

Motivation: Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database.Main Types of Variables Included: The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years.Spatial Location and Grain: Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size.Time Period and Grain: The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric.Major Taxa and Level of Measurement: The database includes any eukaryotic taxa, with a combined total of 56,400 taxa.Software Format: csv and. SQL.

The spatial distribution of environmental conditions can determine where organisms can and cannot live. When the distribution of microhabitats within a landscape is mediated by the shape of its surface, structural complexity can indirectly affect environmental niche distributions. This study investigates how light availability patterns change along a gradient of landscape complexity measured as surface rugosity and height range in tropical shallow reefs. We used 260,000 high frequency and high spatial resolution light measurements across 903 locations to determine the proportion of light that is available at the reef surface. We find that light available on the reef surface is highly variable, with close locations within reef sites experiencing up to 25.7 mol/m ² d of daily photon input difference. After accounting for light attenuation due depth, light availability decreases with increasing surface rugosity: a unit increase in local surface rugosity corresponds to an 11-29% decrease in light availability. Local surface complexity can affect the distributions of light availability at local scales, while broader extent site metrics do not capture this variability. Our results suggest that structural complexity enhances local environmental variability, and its indirect effects on other environmental variables and their interactions are essential for understanding ecosystem processes.

As on land, oceans exhibit high temporal and spatial temperature variation. This “ocean weather” contributes to the physiological and ecological processes that ultimately determine the patterns of species distribution and abundance, yet is often unrecognized, especially in tropical oceans. Here, we tested the paradigm of temperature stability in shallow waters (<12.5 m) across different zones of latitude. We collated hundreds of in situ, high temporal-frequency ocean temperature time series globally to produce an intuitive measure of temperature variability, ranging in scale from quarter-diurnal to annual time spans. To estimate organismal sensitivity of ectotherms (i.e. microbes, algae, and animals whose body temperatures depend upon ocean temperature), we computed the corresponding range of biological rates (such as metabolic rate or photosynthesis) for each time span, assuming an exponential relationship. We found that subtropical regions had the broadest temperature ranges at time spans equal to or shorter than a month, while temperate and tropical systems both exhibited narrow (i.e. stable) short-term temperature range estimates. However, temperature-dependent biological rates in tropical regions displayed greater ranges than in temperate systems. Hence, our results suggest that tropical ectotherms may be relatively more sensitive to short-term thermal variability. We also highlight previously unexplained macroecological patterns that may be underpinned by short-term temperature variability.

It is commonly thought that the biodiversity crisis includes widespread declines in the spatial variation of species composition, called biotic homogenization. Using a typology relating homogenization and differentiation to local and regional diversity changes, we synthesize patterns across 461 metacommunities surveyed for 10 to 91 years, and 64 species checklists (13 to 500+ years). Across all datasets, we found that no change was the most common outcome, but with many instances of homogenization and differentiation. A weak homogenizing trend of a 0.3% increase in species shared among communities/year on average was driven by increased numbers of widespread (high occupancy) species and strongly associated with checklist data that have longer durations and large spatial scales. At smaller spatial and temporal scales, we show that homogenization and differentiation can be driven by changes in the number and spatial distributions of both rare and common species. The multiscale perspective introduced here can help identify scale-dependent drivers underpinning biotic differentiation and homogenization.