2022
DOI: 10.1016/j.marenvres.2021.105537
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Spatial patchiness in change, recruitment, and recovery on coral reefs at Lizard Island following consecutive bleaching events

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Cited by 20 publications
(19 citation statements)
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“…Model assumptions were validated with residual plots. All analyses were conducted in R (R Team, 2020) with the lmer function from the "lme4" package (Bates, Mächler, et al, 2015). The predicted categorical estimates and confidence intervals of the models were calculated using the ggpredict function from the "ggeffects" package in R (Lüdecke, 2018).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Model assumptions were validated with residual plots. All analyses were conducted in R (R Team, 2020) with the lmer function from the "lme4" package (Bates, Mächler, et al, 2015). The predicted categorical estimates and confidence intervals of the models were calculated using the ggpredict function from the "ggeffects" package in R (Lüdecke, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…However, these acclimatization processes may vary among reef zones (Tebbett et al, 2022) and there is growing uncertainty regarding whether corals will resist or acclimatize to the impacts of thermal stress given a lengthening of warm periods and a shortening of the intervals between them (Li & Donner, 2022). Moreover, reefs that experience more infrequent bleaching events are more susceptible to coral loss .…”
Section: Discussionmentioning
confidence: 99%
“…For example, shifts in gene expression enable corals to acclimate to thermal stress (22,32). Such acclimatization processes can be anticipated at community scales and may vary among reef zones (33) or even regions such as the reefs of the eastern tropical Paci c, which have shown to be highly resilient after encountering acute thermal stress (34). Moreover, some studies have found that reefs that experience more infrequent bleaching events are more susceptible to coral loss than reefs that experience more frequent disturbances (23,35).…”
Section: Discussionmentioning
confidence: 99%
“…This motivates the development of spatially-explicit frameworks that can better accommodate the fine spatial scale variability of community assemblages, recovery rates and susceptibility to a disturbance and provide management-ready products to inform effective decision-making. Spatial patterns of coral reef recovery are driven by many variables acting at different spatial scales, including aspects of recent and past disturbance(s) (Connell et al, 1997;Graham et al, 2011;Ortiz et al, 2018;, community structure and demographic processes (Gilmour et al, 2013;Adjeroud et al, 2017;Kayal et al, 2018;Holbrook et al, 2018;Darling et al, 2019), and the environmental climatology of the habitats (Connell et al, 1997;Gouezo et al, 2019;Castro-Sanguino et al, 2021;Tebbett et al, 2022). Combined, this knowl-edge enables more accurate prediction of recovery dynamics of different populations and communities within a reef.…”
Section: Introductionmentioning
confidence: 99%
“…However, these spatial patterns are typically estimated at discrete hierarchical spatial scales, including sites, reefs, habitats and regions to accommodate a high variability of recovery patterns within a reef (Hughes et al, 2012;Tebbett et al, 2022). The systematic lack of studies accounting for fine-scale variability highlights the need to explore the influence of space in the estimations of coral reef recovery patterns to support model-based decision-support that better aligns with management goals (Zurell et al, 2022).…”
Section: Introductionmentioning
confidence: 99%