Biology subjects

Stuart-Smith, R.

Publications and source records attributed to Stuart-Smith, R..

4 recordsLinked to original sources

bioRxiv2025

Assessing predictive accuracy of species abundance models in dynamic systems

Cascading human pressures and environmental change are affecting the natural dynamics of animal populations. Forecasting population abundances from time-series data provides an important avenue for testing competing ecological theories, and for supporting conservation planning and sustainable use, yet changing system dynamics may lead to erroneous predictions. Predictions from a model fitted and tested on historical system dynamics may become irrelevant if system dynamics change. Here we describe methods to test forecast skill in a rapidly changing system where model parameters are likely to be non-stationary. We presented two ways to split time-series into training and test datasets so that training data were: 1) contemporary to the testing data ( modern split), and 2) not contemporary to the testing data ( legacy split). As a case-study, we use animal abundance data from a 30-year time-series from a global warming hotspot. We tested our approach on four temperate reef species with different temporal trends. The case-study and simulation tests confirmed larger forecast errors in legacy split when compared to the modern split. We found that the legacy split had errors that could be more than for times larger for a species that had a rapid collapse in abundance and non-stationary population dynamics. As expected for the species with rapid collapse, the legacy split estimated much higher forecast error than the modern split. Our approach is applicable to a large range of species and systems, including fisheries and threatened species population monitoring, where rapidly changing environments present threats to both the species and management efficacy. Accumulated lessons from across species and systems should shed light on critical generalities that precede broader ecosystem change.

ecology↗

bioRxiv2022

Sustainable reference points for multispecies coral reef fisheries

Sustainably managing fisheries requires regular and reliable evaluation of stock status. However, most multispecies reef fisheries around the globe tend to be data-poor and lack research and monitoring capacity (e.g., long-term fishery data), preventing the estimation of sustainable reference points against which stocks can be assessed. Here, combining fish biomass data for more than 2000 coral reefs with catch estimates from 99 jurisdictions, we estimate site-specific sustainable reference points for coral reef fisheries and use these to assess the status of coral reef fish stocks. We reveal that more than half of jurisdictions with available information have stocks of conservation concern, having failed at least one fisheries sustainability benchmark. We quantify the trade-offs between biodiversity, mean fish length, and ecosystem functions relative to key benchmarks and highlight the ecological benefits of increasing sustainability. Our approach yields multispecies sustainable reference points for coral reef fisheries using environmental conditions, a promising means for enhancing the sustainability of the worlds coral reef fisheries. TeaserA global assessment of the sustainability of multispecies reef fisheries indicates that more than half of jurisdictions have failed at least one of two key sustainability benchmarks.

ecology↗

bioRxiv2022

Changes in benthic and pelagic production interact with warming to drive responses to climate change in a temperate coastal ecosystem

Changing sea temperatures and primary productivity are rapidly altering marine ecosystems, but with considerable uncertainty in our understanding of the relative importance of these drivers and how their interactions may affect fisheries yield through complex food webs. Such outcomes are more difficult to predict for shallow coastal ecosystems than those in pelagic and shelf habitats, because coastal food webs are fuelled by a combination of separate pelagic and benthic energy pathways. Using long-term, empirical field data, we developed a novel multispecies size spectrum model for shallow coastal reefs. We include size-structured benthic and pelagic resources and trophic structures, allowing us to explore potential climate change scenarios that involve varying combinations of warming with changes in benthic and pelagic resources. Our model predicts that changes in resource levels will have much stronger impacts on fish biomass and yields than changes driven by physiological responses to temperature. Under increased plankton abundance, species in all trophic groups were predicted to increase in biomass, average size and yields. By contrast, changes in benthic resource produced variable responses across coastal trophic groups. Increased benthic resource led to increasing benthivorous and piscivorous fish biomass, yields and mean body sizes, but decreases in herbivores and planktivores. When resource changes were combined with warming seas, physiological responses generally decreased species biomass and yields. Our results suggest that the source, size and abundance of primary and secondary producers are critical to understanding impacts of warming seas on coastal fish communities. Understanding changes in benthic production and its implications for coastal fisheries requires urgent attention. Our modified size spectrum model provides a framework for further study of benthic and pelagic energy pathways that can be easily adapted to other ecosystems.

ecology↗

bioRxiv2020

Global gut content data synthesis and phylogeny delineate reef fish trophic guilds

The diversity of life on our planet has produced a remarkable variety of biological traits that characterize different species. Such traits are widely employed instead of taxonomy to increase our understanding of biodiversity and ecosystem functioning. However, for species trophic niches, one of the most critical aspects of organismal ecology, a paucity of empirical information has led to inconsistent definitions of trophic guilds based on expert opinion. Using coral reef fishes as a model, we show that experts often disagree on the assignment of trophic guilds for the same species. Even when broad categories are assigned, 60% of the evaluated trait schemes disagree on the attribution of trophic categories for at least 20% of the species. This disagreement greatly hampers comparability across studies. Here, we introduce a quantitative, unbiased, and fully reproducible framework to define species trophic guilds based on empirical data. First, we synthesize data from community-wide visual gut content analysis of tropical coral reef fishes, resulting in trophic information from 13,961 individuals belonging to 615 reef fish species across all ocean basins. We then use network analysis to cluster the resulting global bipartite food web into distinct trophic guilds, resulting in eight trophic guilds, and employ a Bayesian phylogenetic model to predict trophic guilds based on phylogeny and maximum body size. Our model achieved a misclassification error of 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, which can be updated as new information becomes available. Although our case study is for reef fishes, the most diverse vertebrate consumer group, our approach can be applied to other organismal groups to advance reproducibility in trait-based ecology. As such, our work provides an empirical and conceptual advancement for trait-based ecology and a viable approach to monitor ecosystem functioning in our changing world.

ecology↗