Robust optima and tolerance ranges of biological indicators: a new method to identify sentinels of global warming

Cristóbal, Elena de las Heras; Ayuso, Sergio Velasco; Justel, Ana; Toro, Manuel

doi:10.1007/s11284-013-1099-9

Cited by 16 publications

(17 citation statements)

References 47 publications

(43 reference statements)

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“…Very few direct associations between OTUs and environmental parameters were detected (n = 325, see supplementary text). However, by estimating robust ecological optima (or niche value) and tolerance ranges (or niche widths) ( 39 ) for each OTU and environmental parameter (see M&M and Table S3), we observed a strong influence of temperature in structuring predicted interactions (Fig. 1A).…”

Section: Resultsmentioning

confidence: 93%

“…Environmental optimum and tolerance range were calculated with the robust optimum (RO) method described in ( 39 ). For each OTU and a selection of environmental parameters, we determined the ecological optimum reflecting the optimal OTU living conditions relative to a given environmental parameter, and a tolerance range around this optimum defined by lower and upper bounds.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Environmental vulnerability of the global ocean plankton community interactome

Chaffron¹,

Delage²,

Budinich³

et al. 2020

Preprint

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Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles, and help regulate climate. Though global surveys are starting to reveal ecological drivers underlying planktonic community structure, and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here we leveraged Tara Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network – the community interactome – and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar), and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change, and forecasted most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios, while identifying plausible plankton bioindicators for ocean monitoring of climate change.

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Section: Resultsmentioning

confidence: 93%

Section: Methodsmentioning

confidence: 99%

Environmental vulnerability of the global ocean plankton community interactome

Chaffron¹,

Delage²,

Budinich³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Very few direct associations between OTUs and environmental parameters were detected ( n = 325; see Supplementary Text). However, by estimating robust ecological optima (niche value) and tolerance ranges (realized niche widths) ( 39 ) for each OTU and environmental parameter (see Materials and Methods and table S3), we observed a strong influence of temperature in structuring predicted interactions ( Fig. 1A ).…”

Section: Resultsmentioning

confidence: 94%

“…Environmental optimum and tolerance range were calculated with the robust optimum method described in ( 39 ). For each OTU and a selection of environmental parameters, we determined the ecological optimum reflecting the optimal OTU living conditions relative to a given environmental parameter and a tolerance range around this optimum defined by lower and upper bounds.…”

Section: Methodsmentioning

confidence: 99%

Environmental vulnerability of the global ocean epipelagic plankton community interactome

et al. 2021

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Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles and help regulate climate. Although global surveys are starting to reveal ecological drivers underlying planktonic community structure and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here, we leveraged Tara Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network—the community interactome—and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar) and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change and forecasted the most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios while identifying plausible plankton bioindicators for ocean monitoring of climate change.

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“…The 102 x 63 matrix was provided as input to FlashWeave v1.0 (74) using default parameters, and visualized in Gephi v. 0.9.2 (75). Then to consider whether the ASVs in the Core80, Dynamic50, or Variable fractions of the SaM were affiliated with particular levels of PalA in the ascidian lobes, PalA niche robust optimum and range were computed using the occurrence and dry weight normalized contextual data (76). Weighted gene correlation network analysis (WGCNA package in R; 77) was used to identify modules and their correlation with PalA levels.…”

Section: Methodsmentioning

confidence: 99%