Antiplasmodial Activities of Homogentisic Acid Derivative Protein Kinase Inhibitors Isolated from a Vanuatu Marine Sponge Pseudoceratina sp.

As part of our search for new antimalarial drugs in South Pacific marine sponges, we have looked for inhibitors of Pfnek-1, a specific protein kinase of Plasmodium falciparum. On the basis of promising activity in a preliminary screening, the ethanolic crude extract of a new species of Pseudoceratina collected in Vanuatu was selected for further investigation. A bioassay-guided fractionation led to the isolation of a derivative of homogentisic acid [methyl (2,4-dibromo-3,6-dihydroxyphenyl)acetate, 4a] which inhibited Pfnek-1 with an IC50 around 1.8 μM. This product was moderately active in vitro against a FcB1 P. falciparum strain (IC50 = 12 μM). From the same sponge, we isolated three known compounds [11,19-dideoxyfistularin-3 (1), 11-deoxyfistularin-3 (2) and dibromo-verongiaquinol (3)] which were inactive against Pfnek-1. Synthesis and biological evaluation of some derivatives of 4a are reported

Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance

Intraguild Predation Dynamics in a Lake Ecosystem Based on a Coupled Hydrodynamic-Ecological Model: The Example of Lake Kinneret (Israel)

The food web of Lake Kinneret contains intraguild predation (IGP). Predatory invertebrates and planktivorous fish both feed on herbivorous zooplankton, while the planktivorous fish also feed on the predatory invertebrates. In this study, a complex mechanistic hydrodynamic-ecological model, coupled to a bioenergetics-based fish population model (DYCD-FISH), was employed with the aim of revealing IGP dynamics. The results indicate that the predation pressure of predatory zooplankton on herbivorous zooplankton varies widely, depending on the season. At the time of its annual peak, it is 10–20 times higher than the fish predation pressure. When the number of fish was significantly higher, as occurs in the lake after atypical meteorological years, the effect was a shift from a bottom-up controlled ecosystem, to the top-down control of planktivorous fish and a significant reduction of predatory and herbivorous zooplankton biomass. Yet, seasonally, the decrease in predatory-zooplankton biomass was followed by a decrease in their predation pressure on herbivorous zooplankton, leading to an increase of herbivorous zooplankton biomass to an extent similar to the base level. The analysis demonstrates the emergence of non-equilibrium IGP dynamics due to intra-annual and inter-annual changes in the physico-chemical characteristics of the lake, and suggests that IGP dynamics should be considered in food web models in order to more accurately capture mass transfer and trophic interactions

Examination of the role of the microbial loop in regulating lake nutrient stoichiometry and phytoplankton dynamics

The recycling of organic material through bacteria and microzooplankton to higher trophic levels, known as the "microbial loop", is an important process in aquatic ecosystems. Here the significance of the microbial loop in influencing nutrient supply to phytoplankton has been investigated in Lake Kinneret (Israel) using a coupled hydrodynamic–ecosystem model. The model was designed to simulate the dynamic cycling of carbon, nitrogen and phosphorus through bacteria, phytoplankton and zooplankton functional groups, with each pool having unique C : N : P dynamics. Three microbial loop sub-model configurations were used to isolate mechanisms by which the microbial loop could influence phytoplankton biomass, considering (i) the role of bacterial mineralisation, (ii) the effect of micrograzer excretion, and (iii) bacterial ability to compete for dissolved inorganic nutrients. The nutrient flux pathways between the abiotic pools and biotic groups and the patterns of biomass and nutrient limitation of the different phytoplankton groups were quantified for the different model configurations. Considerable variation in phytoplankton biomass and dissolved organic matter demonstrated the sensitivity of predictions to assumptions about microbial loop operation and the specific mechanisms by which phytoplankton growth was affected. Comparison of the simulations identified that the microbial loop most significantly altered phytoplankton growth by periodically amplifying internal phosphorus limitation due to bacterial competition for phosphate to satisfy their own stoichiometric requirements. Importantly, each configuration led to a unique prediction of the overall community composition, and we conclude that the microbial loop plays an important role in nutrient recycling by regulating not only the quantity, but also the stoichiometry of available N and P that is available to primary producers. The results demonstrate how commonly employed simplifying assumptions about model structure can lead to large uncertainty in phytoplankton community predictions and highlight the need for aquatic ecosystem models to carefully resolve the variable stoichiometry dynamics of microbial interactions

Challenges and opportunities for integrating lake ecosystem modelling approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem model