Linking climate variability and growth in coral skeletal records from the Great Barrier Reef

Impacts of Coral Growth on Geochemistry: Lessons From the Galápagos Islands

“…13 of 20 to high density. This directionality could result from high-density stress bands during warm events (Cantin & Lough, 2014;, or simply from higher density during warm seasons or years, as has been observed elsewhere (e.g., Buddemeier et al, 1974;Lough & Barnes, 1990;Reed et al, 2019). However, because the correlations between observed SST and density are weak, we cannot conclude that SST-driven density changes account for the Sr/Ca-density relationships seen here.…”

“…This warm SST‐high density relationship matches the direction of Sr/Ca‐density relationships on annual (Figure 5) and monthly (Figure ) time scales in modern corals, with low Sr/Ca (warmer inferred SST) corresponding to high density. This directionality could result from high‐density stress bands during warm events (Cantin & Lough, 2014; D'Olivo & McCulloch, 2017), or simply from higher density during warm seasons or years, as has been observed elsewhere (e.g., Buddemeier et al., 1974; Lough & Barnes, 1990; Reed et al., 2019). However, because the correlations between observed SST and density are weak, we cannot conclude that SST‐driven density changes account for the Sr/Ca‐density relationships seen here.…”

“…This chronological variability translates to a 1 σ annual extension rate uncertainty of up to 26% (Text ). Similar chronological errors can arise from calculating extension rate directly from density banding, especially because the seasonal timing of density banding can vary between sites (Tanzil et al., 2016) or even through time within individual corals (Reed et al., 2019). In contrast, the annual mean density error is no higher than 7%.…”

Assessing the Predictability of an Improved ANFIS Model for Monthly Streamflow Using Lagged Climate Indices as Predictors

“…S mj (28) where S mj is computed such as S but with consideration of the assumption that the best prediction (p f = p v ) is computed when S has a positive value. If it has a negative value, S mj is computed based on the assumption of the worst prediction.…”

“…However, the artificial intelligence models and regression models based on a large climate index have a wide application in the predication of hydrological variables, such as rainfall, streamflow, drought and ground water level [27][28][29][30], and thus, these models based on climate indexes are known to be effective tools for climate studies.…”