This paper analyses six major transitions in watershed management in the Lower Mississippi River from the early 19th century till present. A conceptual framework is developed for analysing the role of visions, agency and niches in water management transitions and applied to a historical case on water management in the Lower Mississippi River. It is shown that water management regimes change over time and that major transitions were preceded by niches, in which new visions were developed and empowered. The case shows that: (i) emerging visions play an important role in guiding transitions; (ii) agency enables the further diffusion of visions and niches; (iii) vision champions play an important role in transitions, but are not decisive; (iv) each transition has led to an extension of the number of societal functions provided, which has led to more complex water management regimes in which functions are combined and integrated; and (v) external landscape factors are important, as they can lead to awareness and urgency in important decision making processes.

The continued exploration of the diversity of lactic acid bacteria in little-studied ecological niches represents a fundamental activity to understand the diffusion and biotechnological significance of this heterogeneous class of prokaryotes. In this study, Lactiplantibacillus plantarum (Lpb. plantarum) strains have been isolated from Tunisian vegetable sources, including fermented olive, fermented pepper and from dead locust intestines, subsequently evaluated for their antimicrobial activity against foodborne pathogenic bacteria, including Escherichia coli O157:H7 CECT 4267 and Listeria monocytogenes CECT 4031, as well as against some fungi, including Penicillium expansum, Aspergilus niger and Botrytis cinerea. In addition, their resistance to the oro-gastro-intestinal transit, aggregation capabilities, biofilm production capacity, adhesion to human enterocyte-like cells and cytotoxicity to colorectal adenocarcinoma cell line were determined. Further, the adhesion to tomatoes and the biocontrol potential on this model food matrix were analyzed. It has been found that all the strains were able to inhibit the indicator growth, mostly through organic acids production. Besides, these strains showed promising probiotic traits, including in vitro tolerance to oro-gastrointestinal conditions, adhesion to abiotic surface and to Caco-2 cells. Moreover, all tested Lpb. plantarum strains were able to adhere to tomatoes with similar rate (4.0-6.0 LogCFU/g tomato). The co-culture of LAB strains with pathogens on tomatoes showed that Lpb. plantarum could be a good candidate to control pathogen growth. Nonetheless, further studies are needed to guarantee their use as probiotic strains for biocontrol on food matrices.

Globally, seagrass meadows provide critical ecosystem services. However, seagrasses are globally degraded at an accelerated rate. The lack of information on seagrass spatial distribution and seagrass health status seriously hinders seagrass conservation and management. Therefore, this study proposes to combine remote sensing big data with a new hybrid machine learning model (RF-SWOA) to predict potential seagrass habitats. The multivariate remote sensing data is used to train the machine learning model, which can improve the prediction accuracy of the model. This study shows that a hybrid machine learning model (RF-SWOA) can predict potential seagrass habitats more accurately and effectively than traditional models. At the same time, it has been shown that the most important factors influencing the potential habitat of seagrass in the Hainan region were the distance from land (38.2%) and the depth of the ocean (25.9%). This paper provides a more accurate machine learning model approach for predicting the distribution of marine species, which can help develop seagrass conservation strategies to restore healthy seagrass ecosystems.