Outstanding challenges in the transferability of ecological models

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their ‘transferability’) undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions

Challenges of transferring models of fish abundance between coral reefs

Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1%  0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fish abundance models. However, observations of these local-scale predictors are often not available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management

Otolith microchemistry suggests probable population structuring in the Indian Ocean for the broadbill swordfish Xiphias gladius

Variation in otolith elemental fingerprints was investigated in the broadbill swordfish (Xiphias gladius) to complement genetic data obtained by next generation sequencing in the framework of a collaborative project on population stock structure of tuna, billfish and sharks of the Indian Ocean (PSTBS-IO). Swordfish specimens for this work were sampled in the southwest (SWI), west central (WCI) and southeast (SEI) regions of the Indian Ocean. A total of 70 otoliths (30 from SWI and 20 from each WCI and SEI) were selected and the elemental signatures of their cores were analysed by LA-ICP-MS to investigate potential differences in spawning origin among regions. Among the 15 chemical elements analysed, only Mg, P, Sr, Ba and B were above detection limits and significantly contributed to the variation in otolith core composition. Based on differences in these five elements, three groups of distinct multi-elemental signatures, denoting potentially discrete spawning origins (SpO), were identified using hierarchical clustering based on Euclidian distances. All SpO identified apparently contributed to the swordfish stocks of the three regions sampled, but in different proportions. SpO-1 was the most common spawning source among the fish sampled (49%); it probably corresponds to the swordfish spawning ground located between northeast Australia and Indonesia. SpO-3 was found to provide 34% of the total fish analysed, but mainly in SWI (53%) and WCI (35%). It could correspond to the spawning grounds reported for the species in the central and southwestern Indian Ocean. Lastly, SpO-2, which contributed to only 17% of the total fish analysed (mainly in SEI and WCI), may correspond to the spawning ground previously reported in the northwestern Indian Ocean, off the Somalian coast. Although our results show mixed origins in the fish sampled at each sampling location, the contrast in otolith core fingerprints between SWI and SEI otoliths suggests differences in main spawning origin, at least for the swordfish captured in these two regions of the Indian Ocean. Additional analyses are needed to consolidate these results, as well as information on the spatiotemporal distribution of chemical tracers in the water masses of the Indian Ocean to assign regions to otolith elemental signatures

Impacts of fishing low-trophic level species on marine ecosystems

Low-trophic level species account for more than 30% of global fisheries production and contribute substantially to global food security. We used a range of ecosystem models to explore the effects of fishing low-trophic level species on marine ecosystems, including marine mammals and seabirds, and on other commercially important species. In five well-studied ecosystems, we found that fishing these species at conventional maximum sustainable yield (MSY) levels can have large impacts on other parts of the ecosystem, particularly when they constitute a high proportion of the biomass in the ecosystem or are highly connected in the food web. Halving exploitation rates would result in much lower impacts on marine ecosystems while still achieving 80% of MSY

Better model transfers require knowledge of mechanisms

No abstract available