Modeling biogeomorphological interactions in underwater nourishments

To prevent sandy coastlines from further erosion, nourishments are executed in which sand is usually put underwater at the foreshore. Waves and currents transport the sand on the beach and in this way stabilize the coastal profile. Little is known about the interactions of these so-called shoreface nourishments with the benthic populations inhabiting the coastal strip. Benthos is affected by the nourishments, but benthic populations could in turn affect the morphological evolution of the nourished coast. Monitoring has shown that the benthic community will mainly recovery after ca. 1 year. However, the impact of benthos on the sediment dynamics and hydrodynamics is unknown. In this paper we focus on tube building worms, which have a large abundance in the foreshore, live in patches of several square meters in diameter and protrude several centimeters from the sediment in the water column. Tube building worms are included in a numerical modeling tool (Delft3D), by explicitly accounting for the influence of cylindrical structures on drag and turbulence by an extra source term of friction force in the momentum equation and an extra source term of Total Kinetic Energy (TKE) and turbulent energy dissipation in the k-ε equations respectively. The model is validated against field and flume experiments and it shows a significant influence on flow velocities near the bed, bed shear stress and bed-load transport rates. Moreover, model results reveal that tube building worms are able to stabilize nourishments and slow down the migration of the outer breaker bar. Present model explorations indicate that future research should focus on the measurement of the patchy distribution of bio-engineers in the foreshore and their impact on the sediment dynamics and hydrodynamics. Such knowledge will enable process based modeling of the spatial and temporal variation in biological activity on the morphological development of the coastal profile and also it will lead to validation of the proposed model with field measurements.</jats:p

Canopy-scale biophysical controls on transpiration and evaporation in the Amazon Basin

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (&#955;ET) and evaporation (&#955;EE) flux components of the terrestrial latent heat flux (&#955;E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on &#955;ET and &#955;EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, &#955;ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on &#955;ET during the wet (rainy) seasons where &#955;ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80&#8239;% of the variances of &#955;ET. However, biophysical control on &#955;ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65&#8239;% of the variances of &#955;ET, and indicates &#955;ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between &#955;ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

The impact of atmospheric reactive nitrogen (N$_{r}$) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC/dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of N$_{r}$ deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet N$_{r}$ deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and N$_{r}$ inputs and losses, these data were also combined with in situ flux measurements of NO, N$_{2}$O and CH$_{4}$ fluxes; soil NO$_{3}$̅ leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from -70 to 826 gCm$^{-2}$ yr$^{-1}$ at total wet+dry inorganic N$_{r}$ deposition rates (N$_{dep}$) of 0.3 to 4.3 gNm$^{-2}$ yr$^{-1}$ and from -4 to 361 g Cm$^{-2}$ yr$^{-1}$ at N$_{dep}$ rates of 0.1 to 3.1 gNm$^{-2}$ yr$^{-1}$ in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO$_{2}$ exchange, while CH$_{4}$ and N$_{2}$O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated N$_{dep}$ where N$_{r}$ leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N$_{2}$ losses by denitrification. Nitrogen losses in the form of NO, N$_{2}$O and especially NO$_{3}$̅ were on average 27%(range 6 %–54 %) of N$_{dep}$ at sites with N$_{dep}$ 3 gNm$^{-2}$ yr$^{-1}$. Such large levels of N$_{r}$ loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with N$_{r}$ deposition up to 2–2.5 gNm$^{-2}$ yr$^{-1}$, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP = GPP ratio). At elevated N$_{dep}$ levels (> 2.5 gNm$^{-2}$ yr$^{-1}$), where inorganic N$_{r}$ losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate N$_{dep}$ levels was partly the result of geographical cross-correlations between N$_{dep}$ and climate, indicating that the actual mean dC/dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. N$_{dep}$

Indexing the Pseudomonas specialized metabolome enabled the discovery of poaeamide B and the bananamides

Pseudomonads are cosmopolitan microorganisms able to produce a wide array of specialized metabolites. These molecules allow Pseudomonas to scavenge nutrients, sense population density and enhance or inhibit growth of competing microorganisms. However, these valuable metabolites are typically characterized one-molecule–one-microbe at a time, instead of being inventoried in large numbers. To index and map the diversity of molecules detected from these organisms, 260 strains of ecologically diverse origins were subjected to mass-spectrometry-based molecular networking. Molecular networking not only enables dereplication of molecules, but also sheds light on their structural relationships. Moreover, it accelerates the discovery of new molecules. Here, by indexing the Pseudomonas specialized metabolome, we report the molecular-networking-based discovery of four molecules and their evolutionary relationships: a poaeamide analogue and a molecular subfamily of cyclic lipopeptides, bananamides 1, 2 and 3. Analysis of their biosynthetic gene cluster shows that it constitutes a distinct evolutionary branch of the Pseudomonas cyclic lipopeptides. Through analysis of an additional 370 extracts of wheat-associated Pseudomonas, we demonstrate how the detailed knowledge from our reference index can be efficiently propagated to annotate complex metabolomic data from other studies, akin to the way in which newly generated genomic information can be compared to data from public databases

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

This is the final version of the article. Available from Wiley via the DOI in this record.Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.This paper is a product of the European Union's Seventh Framework Programme AMAZALERT project (282664). The field data used in this study have been generated by the RAINFOR network, which has been supported by a Gordon and Betty Moore Foundation grant, the European Union's Seventh Framework Programme projects 283080, ‘GEOCARBON’; and 282664, ‘AMAZALERT’; ERC grant ‘Tropical Forests in the Changing Earth System’), and Natural Environment Research Council (NERC) Urgency, Consortium and Standard Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘Niche Evolution of South American Trees’ (NE/I028122/1). Additional data were included from the Tropical Ecology Assessment and Monitoring (TEAM) Network – a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partly funded by these institutions, the Gordon and Betty Moore Foundation, and other donors. Fieldwork was also partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil (CNPq), project Programa de Pesquisas Ecológicas de Longa Duração (PELD-403725/2012-7). A.R. acknowledges funding from the Helmholtz Alliance ‘Remote Sensing and Earth System Dynamics’; L.P., M.P.C. E.A. and M.T. are partially funded by the EU FP7 project ‘ROBIN’ (283093), with co-funding for E.A. from the Dutch Ministry of Economic Affairs (KB-14-003-030); B.C. [was supported in part by the US DOE (BER) NGEE-Tropics project (subcontract to LANL). O.L.P. is supported by an ERC Advanced Grant and is a Royal Society-Wolfson Research Merit Award holder. P.M. acknowledges support from ARC grant FT110100457 and NERC grants NE/J011002/1, and T.R.B. acknowledges support from a Leverhulme Trust Research Fellowship

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions