Predicting potential range shifts using climatic time series and niche models: A Neotropical montane shrew's case

Ecological Informatics, Journal Year: 2023, Volume and Issue: 77, P. 102212 - 102212

Published: July 17, 2023

Language: Английский

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Climate change alters the temporal persistence of coastal-pelagic fishes off eastern Australia

ICES Journal of Marine Science, Journal Year: 2022, Volume and Issue: 79(4), P. 1083 - 1097

Published: Feb. 3, 2022

Abstract The climate-driven redistribution of fisheries species is altering their availability to fishers, necessitating projections redistributions that directly relate future fishing opportunities. We propose a valuable proxy for opportunity the proportion year target are available which can be approximated by temporal persistence suitable habitat in defined regions. Here, we quantify changes (months/year) within five eastern Australian bioregions over period 2010–2060 four coastal-pelagic fishes: bonito (Sarda australis), spotted mackerel (Scomberomorus munroi), Spanish commerson) and dolphinfish (Coryphaena hippurus). When were analysed collectively, significant reduction environmental habitats was evident most equatorward (i.e. Tweed-Moreton) bioregion, while positive increases found poleward (e.g. Batemans Twofold Shelf bioregions). greatest projected bioregion Hawkesbury (+2.2 + 1.5 months/year between 10-year averages centered on 2020 2050, respectively). By demonstrating as measure opportunity, highlight potential this metric an effective means communicating stakeholders need adapt climate change.

Language: Английский

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Toward Regional Marine Ecological Forecasting Using Global Climate Model Predictions From Subseasonal to Decadal Timescales: Bottlenecks and Recommendations

Frontiers in Marine Science, Journal Year: 2022, Volume and Issue: 9

Published: Aug. 1, 2022

This perspective paper discusses how the research community can promote enhancement of marine ecosystem forecasts using physical ocean conditions predicted by global climate models (GCMs). We review major prediction projects and outline new opportunities to achieve skillful biological forecasts. Physical are operationally for subseasonal seasonal timescales, multi-year predictions have been enhanced recently. However, forecasting applications currently limited availability oceanic data; most subseasonal-to-seasonal make only sea-surface temperature (SST) publicly available, though other variables useful also calculated in GCMs. To resolve bottleneck data availability, we recommend that centers increase range available public, perhaps starting with an expanded suite 2-dimensional variables, whose storage requirements much smaller than 3-dimensional variables. Allowing forecast output be downloaded a selected region, rather whole globe, would facilitate uptake. highlight both (e.g., approaches dynamical statistical downscaling) conducting reforecasting experiments) offer lessons learned help guide their development. In order accelerate this area, suggest establishing case studies (i.e., particular events as targets) improve coordination. Advancing our capacity is crucial success UN Decade Ocean Science, which one seven desired outcomes “A Predicted Ocean”.

Language: Английский

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Evaluating the effectiveness of matching the timing of occurrences and environmental data in ecological niche models: Insights for low-dispersing species

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: March 30, 2024

Ecological niche models, crucial for estimating species’ potential distribution under global change, can face reduced accuracy when the timing of occurrence data does not align with environmental data. One solution is to ensure a close temporal match between environment and observation date. While this approach typically recommended highly mobile species, few findings support its use species limited mobility, whose distributions may be responding climate change via local population changes. Additionally, it remains unclear what specific resolution could improve model performance. This study assesses effectiveness matching low Mexican small-eared shrew (Cryptotis mexicanus), by evaluating different resolutions (one-, five-, ten-year averaged data) against standard method (30-year). Occurrences 1971 2000 were used training cross-validation, while those outside range external evaluation. Based on omission rate evaluation occurrences, that matched using prior performed better than 30-year average approach, rest metrics (for any resolution) different. Visual inspection indicated geographic prediction resulting from was as realistic one approach. In contrast, shorter (one five years) resulted in unrealistic estimates. Therefore, occurrences other mobility also performance predictions. correlative identifies time lag climatic changes responses species. Studies select optimal exploring several or available information about change.

Language: Английский

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Global patterns and environmental drivers of suitable habitat for Dentex dentex and Sciaena umbra along the Corsican coast

ICES Journal of Marine Science, Journal Year: 2022, Volume and Issue: 79(9), P. 2461 - 2472

Published: Oct. 18, 2022

Abstract Improving the effectiveness of marine spatial management is crucial to preserve ecosystems and also support fisheries economy. In this study, we aimed determine distribution suitable habitats (spawning nursery sites) Sciaena umbra Dentex dentex using catches data in Corsica Island. Random forest models have been used as they are highly accurate suited predict rare species distribution. Predictive maps based on presence/absence showed a high degree variability between species. Suitable were close shore shallow waters for S. deeper further offshore D. dentex. We observed that spawning sites mainly located west coast, while areas distributed all around island addition, demonstrated important contribution environmental factors local (depth Posidonia oceanica meadows) selection their habitats. Our results provide new knowledge understanding ecological processes such by fish Based information, mapping can be implemented improve resource over long term.

Language: Английский

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