Climatic Niche Shift during Azolla filiculoides Invasion and Its Potential Distribution under Future Scenarios

Rodríguez‐Merino, Argantonio; Fernández‐Zamudio, Rocío; García‐Murillo, Pablo; Muñoz, Jesús

doi:10.3390/plants8100424

Cited by 10 publications

(12 citation statements)

References 67 publications

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“…Use of L‐BIO predictors in ENMs resulted in better fits of MaxEnt models to duckweed species' occurrence records than those fit with standard bioclimatic layers. While such improvements have previously been demonstrated for models of fish distributions (Al‐Chokhachy et al 2013), ENMs of floating aquatic macrophytes tend to use air temperatures (Rodríguez‐Merino et al 2019, Armitage and Jones 2020), which, based on these results, could miscalculate projections of climate change‐driven range shifts or invasion probabilities.…”

Section: Discussionmentioning

confidence: 99%

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

Armitage

2022

Ecography

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In modeling species distributions and population dynamics, spatially-interpolated climatic data are often used as proxies for real, on-the-ground measurements. For shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species' environmental tolerances or population projections -particularly among pleustonic and epilimnetic organisms. Using a global database of millions of daily satellite-derived lake surface water temperatures (LSWT), I trained machine learning models to correct for the correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high-resolution global maps of air-LSWT offsets, corresponding uncertainty measures and derived LSWT-based bioclimatic layers for use by the scientific community. I then compared the performance of these LSWT layers and air temperature-based layers in population dynamic and ecological niche models (ENM). While generally high, the correspondence between air temperature and LSWT was quite variable and often nonlinear depending on the spatial context. These LSWT predictions were better able to capture the modeled population dynamics and geographic distributions of two common aquatic plant species. Further, ENM models trained with LSWT predictors more accurately captured lab-measured thermal response curves. I conclude that these predicted LSWT temperatures perform better than raw air temperatures when used for population projections and environmental niche modeling, and should be used by practitioners to derive more biologically-meaningful results. These global LSWT predictions and corresponding error estimates and bioclimatic layers have been made freely available to all researchers in a permanent archive.

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Section: Discussionmentioning

confidence: 99%

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

Armitage

2022

Ecography

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“…Current climate conditions for both risk assessment areas seem suitable for both Azolla species (Peel et al 2007). Nevertheless, A. filiculoides under climate change scenarios will extend its distribution northwards and at higher altitudes, so that part of the Mediterranean habitats may become unsuitable (Rodríguez-Merino et al 2019). However, the boreal climate type in the mountains of the Mediterranean Region of Croatia matches the climate types of northern Europe, including those of the European Alps under both scenarios (Peel et al 2007;Rubel et al 2017), making these regions particularly suitable for invasion.…”

Section: Discussionmentioning

confidence: 99%

Climate change may exacerbate the risk of invasiveness of non-native aquatic plants: the case of the Pannonian and Mediterranean regions of Croatia

Piria¹,

Radočaj²,

Vilizzi³

et al. 2022

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Non-native aquatic plants are amongst the major threats to freshwater biodiversity and climate change is expected to facilitate their further spread and invasiveness. To date, in Croatia, no complete list of non-native extant and horizon aquatic plants has been compiled nor has a risk screening been performed. To address this knowledge gap, 10 extant and 14 horizon aquatic plant species were screened for their risk of invasiveness in the Pannonian and Mediterranean regions of Croatia under current and predicted (future) climate conditions. Overall, 90% and 60% of the extant species were classified as high risk for the Pannonian and Mediterranean regions, respectively, under both climate scenarios. Of the horizon species, 42% were classified as high risk under current conditions and, under climate change, this proportion increased to 78%. The ‘top invasive’ species (i.e. scored as very high risk) under both climate conditions and for both regions were extant Elodea nuttallii and horizon Lemna aequinoctialis. The horizon Hygrophila polysperma was very high risk for the Mediterranean Region under current climate conditions and for both regions under projected climate conditions. Azolla filiculoides, Elodea canadensis, Egeria densa and Utricularia gibba were also classified as high risk under current climate conditions and, after accounting for climate change, they became of very high risk in both regions. Further, Gymnocoronis spilanthoides and Lemna minuta were found to pose a very high risk under climate change only for the Pannonian Region. It is anticipated that the outcomes of this study will contribute to knowledge of the invasiveness of aquatic plants in different climatic regions and enable prioritisation measures for their control/eradication.

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“…Use of L-BIO predictors in ENMs resulted in better fits of MaxEnt models to duckweed species’ occurrence records than those fit with standard bioclimatic layers. While such improvements have previously been demonstrated for models of fish distributions (Al-Chokhachy et al ., 2013), ENMs of floating aquatic macrophytes tend to use air temperatures (Rodríguez-Merino et al ., 2019; Armitage & Jones, 2020), which, based on these results, could miscalculate projections of climate change-driven range shifts or invasion probabilities.…”

Section: Discussionmentioning

confidence: 99%

Global maps of lake surface water temperatures reveal pitfalls of air-for-water substitutions in ecological prediction

Armitage

2022

Preprint

View full text Add to dashboard Cite

In modeling species distributions and population dynamics, spatially-interpolated climatic data are often used as proxies for real, on-the-ground measurements. For shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species' environmental tolerances or population projections -- particularly among pleustonic and epilimnetic organisms. Using a global database of millions of daily satellite-derived lake surface water temperatures (LSWT), I trained machine learning models to correct for the correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high-resolution global maps of air-LSWT offsets, corresponding uncertainty measures, and derived LSWT-based bioclimatic layers for use by the scientific community. I then compared the performance of these LSWT layers and air temperature-based layers in population dynamic and ecological niche models (ENM). While generally high, the correspondence between air temperature and LSWT was quite variable and often nonlinear depending on the spatial context. These LSWT predictions were better able to capture the modeled population dynamics and geographic distributions of two common aquatic plant species. Further, ENM models trained with LSWT predictors more accurately captured lab-measured thermal response curves. I conclude that these predicted LSWT temperatures perform better than raw air temperatures when used for population projections and environmental niche modeling, and should be used by practitioners to derive more biologically-meaningful results. These global LSWT predictions and corresponding error estimates and bioclimatic layers have been made freely available to all researchers in a permanent archive.

show abstract

Climatic Niche Shift during Azolla filiculoides Invasion and Its Potential Distribution under Future Scenarios

Cited by 10 publications

References 67 publications

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

Climate change may exacerbate the risk of invasiveness of non-native aquatic plants: the case of the Pannonian and Mediterranean regions of Croatia

Global maps of lake surface water temperatures reveal pitfalls of air-for-water substitutions in ecological prediction

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Climatic Niche Shift during Azolla filiculoides Invasion and Its Potential Distribution under Future Scenarios

Cited by 10 publications

References 67 publications

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

﻿Climate change may exacerbate the risk of invasiveness of non-native aquatic plants: the case of the Pannonian and Mediterranean regions of Croatia

Global maps of lake surface water temperatures reveal pitfalls of air-for-water substitutions in ecological prediction

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Climate change may exacerbate the risk of invasiveness of non-native aquatic plants: the case of the Pannonian and Mediterranean regions of Croatia