Sviluppo di reti trofiche della comunità planctonica per caratterizzare lo stato di salute dell'ecosistema marino

Plankton is the basis of the marine trophic web, but it is often difficult to obtain accurate data on interaction and metabolic parameters. For this reason, a newly developed approach is presented. It allows the integration of both ordinal qualitative and quantitative data. Using a Monte Carlo approach, realistic values within the parameter ranges are randomly selected to obtain several realistic food webs with a posteriori checking. In this way, it is possible to observe the resulting parameter distribution and perform statistical tests. This approach was applied to several sites in the Atlantic, and notably the planktonic food webs of the Venice Lagoon and Bermuda. Several uncertainty intervals were applied to metabolic parameters and diets of Atlantic food webs, and after applying whole system indicators, the results of the new approach were compared with the respective original study. The original studies lie in the middle of the distribution of the ensemble of the obtained food webs when the whole system indicators are based on metabolic parameters only, and outside the distribution when they are also based on diet. The new approach was applied to the food webs of the Venice lagoon in July of two different years. Detritus resuspension was a pressure perturbation of the system that increased its resilience at the expense of its efficiency. The approach was also applied to a 26-year time series at the Bermuda site. Despite the decline in phytoplankton biomass due to climate change, the plankton food web shows high resilience to perturbation, thanks to various trophic strategies such as detritivory and mixotrophy. Plankton food webs are therefore a useful tool for analyzing the health of the whole ecosystem and for making predictions.Plankton is the basis of the marine trophic web, but it is often difficult to obtain accurate data on interaction and metabolic parameters. For this reason, a newly developed approach is presented. It allows the integration of both ordinal qualitative and quantitative data. Using a Monte Carlo approach, realistic values within the parameter ranges are randomly selected to obtain several realistic food webs with a posteriori checking. In this way, it is possible to observe the resulting parameter distribution and perform statistical tests. This approach was applied to several sites in the Atlantic, and notably the planktonic food webs of the Venice Lagoon and Bermuda. Several uncertainty intervals were applied to metabolic parameters and diets of Atlantic food webs, and after applying whole system indicators, the results of the new approach were compared with the respective original study. The original studies lie in the middle of the distribution of the ensemble of the obtained food webs when the whole system indicators are based on metabolic parameters only, and outside the distribution when they are also based on diet. The new approach was applied to the food webs of the Venice lagoon in July of two different years. Detritus resuspension was a pressure perturbation of the system that increased its resilience at the expense of its efficiency. The approach was also applied to a 26-year time series at the Bermuda site. Despite the decline in phytoplankton biomass due to climate change, the plankton food web shows high resilience to perturbation, thanks to various trophic strategies such as detritivory and mixotrophy. Plankton food webs are therefore a useful tool for analyzing the health of the whole ecosystem and for making predictions

Building weighted networks for plankton communities from semi-quantitative data

Quantitative weighted network models are valuable approaches widely used for understanding properties of the system, including health and good environmental status of marine ecosystems. Although plankton community data in terms of composition and abundance are widely available additional semi-quantitative ecological information are needed to build weighted networks for plankton communities (D’Alelio et al. 2016a). The goal of this study is the definition of an approach for developing quantitative networks from semi-quantitative data of plankton communities. The approach is based on a controlled interactive process that is used to develop synthetic networks that are then tested for realism using simple and general emerging properties by node and by the whole network as validating tests. We used realistic data of the plankton community that consist of biomass values, realistic ranges of the production rate per unit of biomass as well as rates of mixotrophy (from 0 to 1, with 1 = total phototrophy and 0 = total heterotrophy) specific for all taxa of the plankton community. For each consumer realistic range for consumption per unit of biomass and unassimilated rate were given (D’Alelio et al. 2016b). Furthermore, semi-quantitative indications of the strength of interactions between each taxa were defined (improbable/weak link, likely/ important link, very likely and strong link). An iterative MCMC approach was used by extracting independent and random values for parameters from their range, through a uniform distribution, and assigning random quantitative values of diet proportions (between 0 and 1) constrained by semiquantitative strengths. Synthetic models were tested for their respect of energy conservation principles and physiological realism i.e., maximum gross food conversion efficiency, positive emerging respiration and natural mortality for each living functional group. A large group of valid models (ensemble of 1000 networks) were obtained for each site using the process considering opportunity for some imports to occur or not. Whole network indicators we applied to valid models, e.g., the community primary production and respiration rate (Odum 1969), ascendancy and overhead (Costanza and Mageau 1999). Preliminary results on plankton community networks for a coastal lagoon case study indicate a system, far from its climax, with great potential for further development. The procedure developed could be applied to several marine sites possibly linked to capabilities of the system to provide services

Building weighted networks for plankton communities from semi-quantitative data

Quantitative weighted network models are approaches widely used for understanding properties of the system. Although plankton community data in terms of composition and abundance are widely available, additional semi-quantitative ecological information are needed to build weighted networks. The goal of this study is the definition of an approach for developing quantitative networks from semi-quantitative data of plankton communities. The approach is based on a controlled iterative process that is used to develop synthetic networks that are then tested for realism using simple and general emerging properties by node and by the whole network as validating tests. We used realistic ranges for metabolic parameters of plankton community and we have defined semiquantitative indications of the strength of interactions between each taxa. An iterative MCMC approach was used by extracting random values for parameters from their range, through a uniform distribution, and assigning random quantitative values of diet proportions. A large group of valid models (ensemble of 1000 networks) were obtained for two different years for the Venice lagoon as a case study. Whole network indicators were applied to valid models. Preliminary results indicate a stressed system, dominated by detritus fluxes, so with a low mean trophic level and a high efficiency

Planktonic ecological networks support quantification of changes in ecosystem health and functioning

Abstract Plankton communities are the foundation of marine food webs and have a large effect on the dynamics of entire ecosystems. Changes in physicochemical factors strongly influence planktonic organisms and their turnover rates, making their communities useful for monitoring ecosystem health. We studied and compared the planktonic food webs of Palude della Rosa (Venice Lagoon, Italy) in 2005 and 2007. The food webs were developed using a novel approach based on the Monte Carlo random sampling of parameters within specific and realistic ranges to derive 1000 food webs for July of each year. The consumption flows involving Strombididae, Evadne spp. and Podon spp. were identified as the most important in splitting food webs of the July of the two years. Although functional nodes (FNs) differed both in presence and abundance in July of the two years, the whole system indicators showed very similar results. Sediment resuspension acted as a source of stress for the Venice Lagoon, being the most used resource by consumers while inhibiting primary producers by increasing water turbidity. Primary production in the water column was mainly generated by benthic FNs. Although the system was near an equilibrium point, it tended to increase its resilience at the expense of efficiency due to stress. This study highlights the role of plankton communities, which can serve to assess ecosystem health

Underdiagnosed veno-occlusive disease/sinusoidal obstruction syndrome (VOD/SOS) as a major cause of multi-organ failure in acute leukemia transplant patients: an analysis from the EBMT Acute Leukemia Working Party.

Allogeneic hematopoietic cell transplantation (alloHCT) is a complex, potentially fatal therapy featuring a myriad of complications. Triggering event(s) of such complications vary significantly, but often a so-called "multi-organ failure" (MOF) is reported as the leading cause of death. The identification of the exact trigger of MOF is critical towards early and disease-specific intervention to improve outcome. We examined data from 202 alloHCT patients reported to have died of MOF from the EBMT registry aiming to determine their exact cause of death focusing on veno-occlusive disease/sinusoidal obstruction syndrome (VOD/SOS) due to its life-threatening, often difficult to capture yet preventable nature. We identified a total of 70 patients (35%) for whom VOD/SOS could be considered as trigger for MOF and leading cause of death, among which 48 (69%) were previously undiagnosed. Multivariate analysis highlighted history of hepatic comorbidity or gentuzumab use and disease status beyond CR1 as the only significant factors predictive of VOD/SOS incidence (OR = 6.6; p = 0.001 and OR = 3.3; p = 0.004 respectively). VOD/SOS-related MOF was widely under-reported, accounting for 27% of deaths attributed to MOF of unknown origin without a previous VOD/SOS diagnosis. Our results suggest most missed cases developed late VOD/SOS beyond 21 days post-alloHCT, highlighting the importance of the newly revised EBMT criteria