Engineered Substrates Reveal Species-Specific Inorganic Cues for Coral Larval Settlement

The widespread loss of stony reef-building coral populations has been compounded by pervasive recruitment failure, i.e., the low or absent settlement and survival of coral juveniles. To combat global coral reef stressors and rebuild coral communities, restoration practitioners have developed workflows to rear and settle vulnerable coral larvae in the laboratory and subsequently outplant settled juveniles back to natural and artificial reefs. These workflows often make use of the natural biochemical settlement cues present in crustose coralline algae (CCA), which can be presented to swimming larvae as extracts, fragments, or live algal sheets to induce settlement. In this work, we investigated the potential for inorganic chemical cues to complement these known biochemical effects. We designed settlement substrates made from lime mortar (CaCO3) and varied their composition with the use of synthetic and mineral additives, including sands, glasses, and alkaline earth carbonates. In experiments with larvae of two Caribbean coral species, Acropora palmata (elkhorn coral) and Diploria labyrinthiformis (grooved brain coral), we saw additive-specific settlement preferences (>10-fold settlement increase) in the absence of any external biochemical cues. Interestingly, these settlement trends were independent of bulk surface properties such as surface roughness and wettability. Instead, our results suggest that not only can settling coral larvae sense and positively respond to soluble inorganic materials, but that they can also detect localized topographical features more than an order of magnitude smaller than their body width. Our findings open a new area of research in coral reef restoration, in which engineered substrates can be designed with a combination of organic and inorganic additives to increase larval settlement, and perhaps also improve post-settlement growth, mineralization, and defense

Millimeter-scale ridges increase the duration of larval settling windows.

(a) Visualization of the relative fluid speed over flat (left) and ridged (right) substrates during peak (top) and turning point (bottom) flow. The fluid velocity (U) is normalized by the average larval swimming velocity (uℓ). Dotted black boxes represent regions ≤1.5 mm above the substrate surface that were used to calculate duration of settlement windows. Black arrows near the bottoms of the ridges indicate regions where the velocity remains low even at the turning points. (b) The average relative flow speed within the dotted black regions plotted over an average period for flat (top) and ridged (bottom) substrates. The yellow regions highlight the settling windows during which the local flow speed drops below uℓ (black line) plus one standard deviation (grey band).</p

Estimação de parâmetros genéticos em tamanho de leitegada de suínos utilizando análises de características múltiplas Estimation of genetic parameters for litter size in pigs using multi-trait analyses

Registros de animais da raça Large White foram utilizados para estimar componentes de co-variâncias e parâmetros genéticos para a característica número de leitões nascidos como medida do tamanho de leitegada. Na obtenção dos componentes de co-variâncias e dos parâmetros genéticos, utilizou-se o método da Máxima Verossimilhança Restrita, com o algoritmo Livre de Derivadas, por meio do programa MTDFREML. O modelo misto continha o efeito fixo de grupo contemporâneo e os efeitos aleatórios genético aditivo direto e residual. Dados das primeiras quatro parições foram usados em duas análises: análises unicaracterísticas e análise multicaracterística separada em séries de análises bicaracterísticas, na qual cada parição foi tratada como característica diferente. As estimativas de herdabilidades aditivas diretas para as parições obtidas nas análises multicaracterísticas foram consistentes com as estimativas obtidas nas análises unicaracterísticas, que variaram de 0,14 a 0,20. Estimativas de correlação fenotípica foram menores que as correlações genéticas. As correlações genéticas foram menores que 0,75 em todas as parições, exceto entre a terceira e a quarta parição, cuja correlação foi alta (0,91). A menor correlação genética foi observada entre a primeira e a segunda ordem de parto (0,60).<br>Data from the first four parities of Large White pigs were used to estimate (co)variance components and genetic parameters for litter size (LS) in single trait and multi-trait analyses. The (co)variance components and genetic parameters were estimated by restricted maximum likelihood using the MTDFREML program. LS in each parity was considered a different trait and the models included contemporary group as fixed effect and additive direct genetic and residual as random effects. Heritability estimates of LS in different parities in single trait analyses ranged from 0.14 to 0.20. Estimates of heritability in multi-trait analyses were similar to those obtained in single trait analyses. Phenotypic correlation estimates were lower than the genetic ones. Genetic correlations between parities were lower than 0.75, except for the estimate between the third and fourth parities, which was the highest one (0.91). The smallest genetic correlation (0.60) was observed between the first and second parities