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Seed‐based seagrass restoration strategies demand precise understanding of the environmental drivers influencing flowering. Flowering varies across diverse spatial and temporal scales, yet environmental drivers' effects on these dynamics have received less attention. Lack of knowledge regarding this life‐history stage limits the advancement of seed‐based restoration efforts, especially the establishment of shore‐based seagrass nurseries to enhance seed production.A systematic literature review on the flowering of the genus Zostera was conducted to develop a conceptual model that links influential environmental drivers with flowering. Additionally, a case study using existing survey data supplemented by additional field surveys was designed to explore the spatio‐temporal variability of flowering along the latitudinal gradient in Australasia for the species Zostera muelleri. Predictive models for flowering times were developed using regional climatic variables, following hypotheses generated from long‐term mesocosm observations.The review identified the direct and/or indirect effects of temperature, light, tidal variation, nutrients, salinity and grazing pressure on flowering dynamics. Four categories of flowering variables were identified based on their implications on restoration, namely, timing, abundance, the ratio between reproductive and vegetative growth and morphological characteristics. The spathe densities varied significantly among sites along the latitudinal gradient. While first (r2 = 0.71) and peak (r2 = 0.68) flowering times showed significant correlation with latitude, first flowering was equally predicted by mean winter air temperature and mean winter solar radiation (r2 = 0.73), whereas peak flowering time was best predicted by mean winter air temperature (r2 = 0.60).Accurate predictions of flowering times can improve conservation outcomes by enabling restoration practitioners to forecast flowering times and subsequent wild seed harvesting. The strong correlation between flowering times and climatic variables suggests future shifts in flowering times under climate change are likely, which is crucial knowledge for maintaining the contribution of restoration projects to seagrass conservation. [ABSTRACT FROM AUTHOR]

Aim Cumulative impact maps are used to identify the spatial distribution of multiple human impacts to species and ecosystems. Impacts can be caused by local stressors which can be managed, such as eutrophication, and by global stressors that cannot be managed, such as climate change. Cumulative impact maps typically assume that there are no interactive effects between stressors on biodiversity. However, the benefits of managing the ecosystem are affected by interactions between stressors. Our aim was to determine whether the assumption of no interactions in impact maps leads to incorrect identification of sites for management. Location General, Australasia. Methods We used the additive effects model to incorporate the effects of interactions into an interactive impact map. Seagrass meadows in Australasia threatened by a local stressor, nutrient inputs, and a global stressor, warming, were used as a case study. The reduction in the impact index was quantified for reductions in the nutrient stressor. We examined the outcomes for three scenarios: no interactions, antagonistic interactions or synergistic interactions. Results Cumulative impact maps imply that reducing a local stressor will give equivalent reductions in the impact index everywhere, regardless of spatial variability in a global stressor. We show that reductions in the impact index were greatest in refuges from warming if there was an antagonistic interaction between stressors, and greatest in areas of high warming stress if there was a synergistic interaction. Reducing the nutrient stressor in refuges from warming always reduced the impact index, regardless of the interaction. Main conclusions Interactions between local and global stressors should be considered when using cumulative impact maps to identify sites where management of a local stressor will provide the greatest impact reduction. If the interaction type is unknown, impact maps can be used to identify refuges from global stressors, as sites for management. [ABSTRACT FROM AUTHOR]