Damage or benefit? How future scenarios of climate change may affect the distribution of small pelagic fishes in the coastal seas of the Americas

Guerra, Thiago Pereira; Santos, Josiene Maria Falcão Fraga dos; Pennino, María Grazia; Lopes, Priscila F. M.

doi:10.1016/j.fishres.2020.105815

Cited by 9 publications

(6 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The use of Species Distribution Models (SDMs) to predict current and future distribution ranges of marine organisms has increased substantially since the mid-2010s (Robinson et al, 2017;Guerra et al, 2021;Hernández-Ucera et al, 2021;Pickens et al, 2021). SDMs rely on the relationship between a species' georeferenced record (e.g., presence/absence data) and environmental variables to predict the probability of being found elsewhere (Robinson et al, 2017).…”

Section: Species Datamentioning

confidence: 99%

“…The first three variables were downloaded as mean for the surface marine realm and the latter as mean depth. We used depth to estimate rugosity, an index often used to predict species distribution and suitable habitats, as well as an indicator of hardbottom habitat (seafloor heterogeneity) (Dunn and Halpin, 2009;McArthur et al, 2010;Fonseca et al, 2017;Guerra et al, 2021). The rugosity index was derived from the depth layer using the 'Terrain Ruggedness Index' of the raster package in the R software (R Core Team, 2021).…”

Section: Environmental Predictor Variablesmentioning

confidence: 99%

“…The distribution of marine species can be influenced by several environmental predictors. However, only to five variables can accurately predict the current and future distributions of marine species (Lezama-Ochoa et al, 2016;Zhang et al, 2019;Guerra et al, 2021;Hernańdez-Ucera et al, 2021). Temperature, salinity, current velocity, primary productivity, and seafloor parameters (e.g., slope, roughness, rugosity) are amongst the most informative predictors used in species distribution models in marine ecosystems (Bosch et al, 2018;Guerra et al, 2021;Pickens et al, 2021).…”

Section: Model Performance and Effect Of Covariatementioning

confidence: 99%

“…However, only to five variables can accurately predict the current and future distributions of marine species (Lezama-Ochoa et al, 2016;Zhang et al, 2019;Guerra et al, 2021;Hernańdez-Ucera et al, 2021). Temperature, salinity, current velocity, primary productivity, and seafloor parameters (e.g., slope, roughness, rugosity) are amongst the most informative predictors used in species distribution models in marine ecosystems (Bosch et al, 2018;Guerra et al, 2021;Pickens et al, 2021). Water temperature was the most informative environmental variable in controlling the potential distribution of the Atlantic blue crab, which aligns with the species' temperature-dependent trait (Brylawski and Miller, 2006;Hines, 2007;Hines et al, 2010;Azra et al, 2020;Rogers et al, 2022).…”

Section: Model Performance and Effect Of Covariatementioning

confidence: 99%

“…We hypothesize that 1) water temperature will be closely related to the distribution of the Atlantic blue crab in native and non-native habitats and 2) rising ocean temperature will reshape the current distribution. To test our hypotheses, we used Species Distribution Modeling (SDM) because it allows for addressing issues in conservation planning (Franklin, 2013;Villero et al, 2017), evolution (Pinsky et al, 2020), biogeography (Torn et al, 2020Pickens et al, 2021), invasiveness potential of non-native species (Jimeńez-Valverde et al, 2011;Mainali et al, 2015), and even inferring the impacts of climate change on species distribution (Lezama-Ochoa et al, 2016;Zhang et al, 2019;Guerra et al, 2021). We chose BARTs because it is a flexible SDM tool offering a wide range of options to extract relationships between species and abiotic conditions, elucidating the roles of predictive variables in determining species distributions, environmental condition preferences (twodimensional range of environmental conditions where the species showed the highest probabilities of presence), posterior distributions on predictions as a measure of uncertainty, and optimal spatial locations for species expansion or invasion (Chipman et al, 2010;Carlson, 2020;Carlson et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Aquatic species shows asymmetric distribution range shifts in native and non-native areas

et al. 2023

View full text Add to dashboard Cite

IntroductionClimate change is reshaping the geographical distribution of species across the globe. In marine ecosystems, climate change creates novel challenges to an environment impacted by numerous anthropogenic stressors. Forecasting shifts in species distribution, including the expansion of non-indigenous species under climate change scenarios, is a management challenge for today’s world.MethodsWe applied Bayesian Additive Regression Tree (BART) models to investigate the environmental factors modulating the occurrence and habitat preferences of the Atlantic blue crab Callinectes sapidus Rathbun, 1896 in native and non-native areas. With BART models, we also aimed to predict its current and future distributions under two climate change scenarios (RCPs 4.5 and 8.5). BART models were performed using global occurrences of the Atlantic blue crab – recorded from 1830 to 2022 – and several environmental covariates (i.e., water temperature, salinity, current velocity, and rugosity). Model accuracy was assessed with the Area Under the Curve (AUC) and True Skill Statistics (TSS) criteria. Cross-validation experiments were made to balance accuracy prediction and uncertainty model prediction intervals.Results and discussionAUC and TSS values indicated that data validation was successful for the BART model. Water temperature was the most critical variable affecting the presence probability of the Atlantic blue crab. The BART model predicts asymmetric distribution range shifts on both sides of the Atlantic Ocean. The non-native populations will experience broader shifts in their distribution range than in the native range, and the RCP 8.5 scenario model outputs predict a wider distribution range by the end of the century. Overall, we anticipate significant ecological changes in native and non-native areas. The range expansion in native areas is often equivalent to the ecological shifts induced by invasive species, so lessons learned by ecologists and managers in non-native areas will provide actionable insights to managers in native areas.

show abstract

Section: Species Datamentioning

confidence: 99%

Section: Environmental Predictor Variablesmentioning

confidence: 99%

Section: Model Performance and Effect Of Covariatementioning

confidence: 99%

Section: Model Performance and Effect Of Covariatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Aquatic species shows asymmetric distribution range shifts in native and non-native areas

et al. 2023

View full text Add to dashboard Cite

show abstract

Incorporating mesopelagic fish into the evaluation of conservation areas for marine living resources under climate change scenarios

Liu

Teschke

et al. 2023

Mar Life Sci Technol

View full text Add to dashboard Cite

Mesopelagic fish (meso-fish) are central species within the Southern Ocean (SO). However, their ecosystem role and adaptive capacity to climate change are rarely integrated into marine protected area (MPAs) assessments. This is a pity given their importance as crucial prey and predators in food webs, coupled with the impacts of climate change. Here, we estimate the habitat distribution of nine meso-fish using an ensemble model approach (MAXENT, random forest, and boosted regression tree). Four climate model simulations were used to project their distribution under two representative concentration pathways (RCP4.5 and RCP8.5) for short-term (2006–2055) and long-term (2050–2099) periods. In addition, we assess the ecological representativeness of established and proposed MPAs under climate change scenarios using meso-fish as indicator species. Our models show that all species shift poleward in the future. Lanternfishes (family Myctophidae) are predicted to migrate poleward more than other families (Paralepididae, Nototheniidae, Bathylagidae, and Gonostomatidae). In comparison, lanternfishes were projected to increase habitat area in the eastern SO but lose area in the western SO; the opposite was projected for species in other families. Important areas (IAs) of meso-fish are mainly distributed near the Antarctic Peninsula and East Antarctica. Proposed MPAs cover 23% of IAs at present and 38% of IAs in the future (RCP8.5, long-term future). Many IAs of meso-fish still need to be included in MPA proposals, such as the Prydz Bay and the seas around the Antarctic Peninsula. Our results provide a framework for designing new MPAs incorporating climate change adaptation strategies for MPA management.

show abstract

Climate Change Impacts on the Nursery Function for Fish of Coastal Zones

Cabral

2024

Treatise on Estuarine and Coastal Science (Second Edition)

View full text Add to dashboard Cite

Damage or benefit? How future scenarios of climate change may affect the distribution of small pelagic fishes in the coastal seas of the Americas

Cited by 9 publications

References 57 publications

Aquatic species shows asymmetric distribution range shifts in native and non-native areas

Aquatic species shows asymmetric distribution range shifts in native and non-native areas

Incorporating mesopelagic fish into the evaluation of conservation areas for marine living resources under climate change scenarios

Climate Change Impacts on the Nursery Function for Fish of Coastal Zones

Contact Info

Product

Resources

About