Water hyacinth (WH) is notorious for causing severe environmental degradation and being an economic burden to manage. However, it offers substantial prospects if exploited, especially by rural communities. High temperatures, eutrophic conditions and other environmental factors promote the proliferation of the plant in regions where it has been introduced. Regarded as among the world’s worst invasive weeds, WH is nearly impossible to control and eradicate without an integrated approach and community participation. The effectiveness of control methods varies, yet sustained community involvement determines the long-term success of these methods. Reproducing rapidly, WH has the resource capacity to support a unique microeconomic ecosystem, incentivising WH control by generating sustainable income. The WH ecology, the socioeconomic impacts of its invasion and its various applications are reviewed, and revenue generation and cost-saving options are highlighted. A circular microeconomic model is proposed by integrating WH valorisation into the general limitations of a rural community. Empowering locals with opportunities and enticing them with potential economic gains can be a nudge towards a pro-environment behavioural change in managing WH. This would aid in upgrading local livelihoods and could foster resilience within the community in tackling both environmental problems and economic setbacks through the management of WH invasions.

Pandoraea sp. strain SD6-2 is a δ-hexachlorocyclohexane-degrading bacterial strain isolated from lindane-contaminated soil in Queensland, Australia. The genome of SD6-2 was sequenced to investigate its ability to degrade δ-hexachlorocyclohexane. Here we report the annotated genome sequence of this strain.

Ralstonia sp. strain GA3-3 is a hexachlorocyclohexane (HCH)-degrading bacterial strain isolated from suburban soil in Canberra, Australia. The genome of strain GA3-3 was sequenced to investigate its ability to degrade α-HCH. Here, we report the annotated genome sequence of this strain.

Nonlinear growth modeling can offer a more robust approach in curve fitting exercises compared to the traditional linear regression for modelling microbial growth processes. The models utilized include Huang, Baranyi-Roberts, modified Gompertz, Buchanan-3-phase, modified Richards, modified Schnute, modified Logistics, von Bertalanffy, MMF (Morgan Mercer Flodin), and the study evaluated these primary growth models to describe a bacterial consortium growth on lindane, with growth measured indirectly by chloride release. The results show that choosing the best model using visual inspection is inadequate for distinguishing between models, as all evaluated models demonstrated acceptable fits. A statistically and information-criterion-based discriminatory approach demonstrated distinct performance disparities. The Huang model consistently demonstrated superior performance compared to competing models, characterized by the lowest error values, the highest explanatory power, favorable information criteria, and minimal systematic bias. However, the modified Richards and modified Logistics models also exhibited competitive performance under specific criteria. The MOORA multi-criteria decision-making approach was utilized to mitigate the uncertainty associated with the majority voting approach. MOORA demonstrates that the Huang model is the most robust overall, with the modified Richards and modified Logistics models following closely behind. The parameters obtained from the Huang model for the chloride release kinetics at 10 μM lindane were Lag period (d or day), Ymax, and μm values of -3.132 (d), 9.235, and 0.934 (d-1), respectively. The utilization of the modelling exercise yielded important parameters for future secondary modelling exercises and preliminary prediction of performance and limitations in field studies.