Search

Framework-forming cold-water corals are ecosystem engineers that build mounds in the deep-sea that can be several hundred meters high. The effect of the presence of cold-water coral mounds on their surrounding is typically difficult to separate from environmental factors that are not affected by the mounds. We investigated the environmental control on cold-water coral reefs at multiple spatial scales, using annotated video transects data, spatial variables (MEMs) and hydrodynamic model output in a redundancy analysis and with variance partitioning. Using available hydrodynamic simulations with cold-water coral mounds and simulations where the mounds were artificially removed, we investigated the effect of coral mound ecosystem engineering on the spatial configuration of reef habitat and discriminated which environmental factors are and which are not affected by the mounds. We find that, due to the interaction between the coral mound and the water flow, different hydrodynamic zones are created on a coral mound that likely determine the typical benthic zonation of coral rubble at the mound foot, dead coral framework on the mound flank, and living corals near the summit. Moreover, we observed a so-called massenerhebung effect (well-known for terrestrial mountains) meaning that benthic zonation depends on the location on the mound rather than on the height above the seafloor or water depth. Our finding that ecosystem engineering determines the configuration of benthic habitats on cold-water coral mounds has many implications, such as that cold-water corals cannot simply move towards deeper water depths to avoid the adverse effects of climate change. We further find that downward velocities in winter, related to non-engineered environmental factors, e.g., deep winter mixing and dense water cascading, correlated to substantial differences in reef cover at the broadest spatial scale (20–30 km). Such hydrodynamic processes that stimulate the food supply towards the corals in winter are more important for the reefs than similar hydrodynamic processes in summer. There is much research on the ecosystem engineering effects of cold-water corals, but our results highlight that the influence of non-engineered environmental processes that accelerate the food supply towards the cold-water corals should not be underestimated.

Fire has been an integral evolutionary force shaping and maintaining grassy biomes, such as the Afromontane grasslands of South Africa. Afromontane grasslands represent a large carbon reservoir, but it is uncertain how fire affects their long-term C storage. We investigated the effect of fire regime on soil organic C and N (SOC; SON) in a long-term (39-year) burning experiment in the Maloti-Drakensberg Park, South Africa. We compared SOC and SON sampled in 2004 and 2019 from six treatments differing in fire frequency (annual, biennial, five-year, infrequent) and season (spring, autumn). Average SOC increased significantly between 2004 and 2019. Average SON increased slightly, resulting in a significant increase in C:N ratio, indicating that soil organic matter is becoming less N-eutrophic. Importantly, burning annually in spring increased SOC and SON. This unexpected response is attributed to the aluandic (acidic, high organic matter) properties of Drakensberg soils. Burning in autumn did not increase SOC and SON. The lowest C stocks were observed in infrequently burnt plots. Average C sequestration across all fire treatments was 0.30 Mg ha���1 y���1. The observed increase in SOC under frequent fires is contrary to many findings from other studies in grassy ecosystems and notably driven by fire season.

Canopy structure alters net precipitation inputs, partly governing the quantity of water recharging soil moisture. Clumped and scattered shrublands are structured with aggregated and isolated canopies, respectively, demonstrating contrasting self-organized patterns. However, the influence of self-organization on rain harvesting is largely unknown. Hence, we compared rainfall redistribution patterns of different self-organized shrubs of Vitex negundo and soil moisture responses during the 2020–2021 rainy seasons on the Loess Plateau of China. Our results indicated that the scattered shrubs harvested more throughfall (85.6% vs. 74.7%) and net precipitation (90.8% vs. 83.8%) than clumped shrubs. Comparatively, stemflow of clumped shrubs was initiated (57.2 vs. 60.4 min) and peaked (198.9 vs. 207.7 min) earlier, ceased later (84.4 vs. 54.5 min), lasted longer (8.9 vs. 8.4 hr), transported more swiftly (397.0 vs. 373.8 mm h−1), and yielded a larger quantity (400.8 vs. 355.1 mL), respectively. This flux was funneled more efficiently (160.1 versus 140.5 fold compared to rain), and was more productive (1.768 vs. 1.346 mm g−1) per unit biomass investment. For both self-organized patterns, more throughfall led to wetter soils, but more stemflow resulted in quicker response of soil moisture. Comparatively, the top-layer soil moisture remained more stable post rain under clumped shrubs. Therefore, via rainfall partitioning, the scattered organization was conducive for V. negundo to harvest more rain, but the clumped shrubs harvested rain more efficiently. This might relate to morphological adaptations of shrubs to resist drought and consequent formation and maintenance of self-organizations at the landscape scale.

The authors want to inform you about the following two errors in the paper ‘Feedbacks between hydrodynamics and cold-water coral mound development’: 1. During formatting by the journal, a problem occurred with equations (4)–(7) and references to the equations in the text. In particular, the brackets indicating time-averaging disappeared in the published version of the manuscript. The full paragraph should read as follows. “The energy conversion rate is calculated as (Gerkema et al., 2004; Gerkema, 2019): [Formula presented]with: [Formula presented] Here [Formula presented]is time and the averaging interval [Formula presented]is taken as one tidal cycle. [Formula presented]has units of W m-3. We used the potential density in the calculation (4), because this is the quantity available from the model. This is however equivalent to using the perturbation density [Formula presented](as in (4), via [Formula presented]. Introducing [Formula presented]based on the potential density, we find: [Formula presented] [Formula presented] [Formula presented] Since [Formula presented]and [Formula presented]is time-independent, the first term on the right side of (7) disappears and hence [Formula presented]” 2. There was an error in the units of Figs. 5 and 6. The units reported in Fig. 5 for turbulent energy dissipation rates should be W/kg instead of W/m3. Fig. 6 shows the depth-integrated turbulent energy dissipation rates, so here the units need to be Wm/kg. The unit error has no consequences for the conclusions of the paper, since we only compare the results qualitatively within our own simulations. We would like to make a further clarification regarding the values of the turbulent energy dissipation rates. Our turbulent energy dissipation values are low when compared to measured dissipation rates, because of three reasons. First, we smoothened the bathymetry to study the dynamics around a coral mound without the effects of nearby protrusions. Furthermore, we calculated the dissipation rates at relatively coarse spatial scales of 250m (i.e. the model resolution) in the horizontal and up to 6m in the vertical (near the surface and bottom over steep topography), whereas turbulent dissipation rates are typically measured at scales of O(cm). Lastly, we used the classical formulation for turbulent energy dissipation by Thorpe (2007). Values for kinetic energy dissipation at the scales of our model could more realistically be calculated with other formulations that account for the larger spatial scale and the difference in horizontal and vertical scales (e.g. MacKinnon and Gregg, 2003; Nikurashin et al., 2013), if a comparison with measured values or other studies is to be made (which was not the purpose of our study). We thank Prof. Daniel Bourgault, Institut des Sciences de la Mer de Rimouski (ISMR), for bringing these issues to our attention. References Gerkema T (2019) An Introduction to Tides. Cambridge University Press Gerkema T, Lam FPA, Maas LRM (2004) Internal tides in the Bay of Biscay: Conversion rates and seasonal effects. Deep Res Part II Top Stud Oceanogr 51:2995–3008 MacKinnon JA, Gregg MC (2003) Mixing on the late-summer new England shelf-Solibores, shear, and stratification. J Phys Oceanogr 33:1476–1492 Nikurashin M, Vallis GK, Adcroft A (2013) Routes to energy dissipation for geostrophic flows in the Southern Ocean. Nat Geosci 6:48–51 Thorpe SA (2007) An Introduction to Ocean Turbulence. Cambridge University Press