2022
DOI: 10.1016/j.ecoinf.2022.101682
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Species distribution modeling and machine learning in assessing the potential distribution of freshwater zooplankton in Northern Italy

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Cited by 6 publications
(3 citation statements)
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“…Now, the question is to what extent a bivoltine life cycle, WGP and TGP bounce back and/or weaken patterns represent a bet hedging strategy or a maladaptation. A model to simulate and compare univoltine and bivoltine life cycles of E. virens in predictable and unpredictable changing hydroperiod is needed to confirm our hypothesis and to evaluate the possible impact of warmer winter and drought due to climate change (Bellin & Rossi, 2024;Bellin et al, 2021Bellin et al, , 2022.…”
Section: Resultsmentioning
confidence: 96%
“…Now, the question is to what extent a bivoltine life cycle, WGP and TGP bounce back and/or weaken patterns represent a bet hedging strategy or a maladaptation. A model to simulate and compare univoltine and bivoltine life cycles of E. virens in predictable and unpredictable changing hydroperiod is needed to confirm our hypothesis and to evaluate the possible impact of warmer winter and drought due to climate change (Bellin & Rossi, 2024;Bellin et al, 2021Bellin et al, , 2022.…”
Section: Resultsmentioning
confidence: 96%
“…For each of the three gorgonian species, the partial response curve of the most important environmental variable was estimated considering the others as xed at their mean value and the environmental variable that showed the highest second order interaction term with the most important one was xed at the extremes and at the mean value of the environmental gradient (Bellin et al 2022).…”
Section: Pseudo-absences Generationmentioning
confidence: 99%
“…The distribution and abundance of gorgonians are increasingly threatened by several stressors, including global warming, seawater carbonate chemistry, the spread of alien species, and local anthropogenic activities (Cerrano et Here we explore a species distribution model framework combined with machine learning algorithms, to assess the potential environmental drivers that shape the distribution and habitat suitability at regional level of three gorgonian species P. clavata, E. cavolinii and E. singularis in the Mediterranean Sea. The modelling framework was used to identify the location and overlap of vulnerable habitats or areas in need of further sampling and to predict their future habitat suitability under the worst IPCC scenario RCP8.5 (Bellin et al 2022). Understanding of the distribution patterns of species in space and time is crucial for the identi cation of sites of special interest both inside and outside of existing marine protect areas and in the establishment of management and conservation actions and strategies (Fortin and Dale 2005).…”
Section: Introductionmentioning
confidence: 99%