Elevated carbon dioxide and reduced salinity enhance mangrove seedling establishment in an artificial saltmarsh community.

The global phenomenon of mangrove encroachment into saltmarshes has been observed across five continents. It has been proposed that this encroachment is driven in part by rising atmospheric CO2 concentration and reduced salinity in saltmarshes resulting from rising sea levels enhancing the establishment success of mangrove seedlings. However, this theory is yet to be empirically tested at the community-level. In this study, we examined the effect of CO2 and salinity on seedling growth of two mangrove species, Aegiceras corniculatum and Avicennia marina, grown individually and in a model saltmarsh community in a glasshouse experiment. We found that the shoot (210%) and root (91%) biomass of the saltmarsh species was significantly greater under elevated CO2. As a result, both mangrove species experienced a stronger competitive effect from the saltmarsh species under elevated CO2. Nevertheless, A. marina seedlings produced on average 48% more biomass under elevated CO2 when grown in competition with the saltmarsh species. The seedlings tended to allocate this additional biomass to growing taller suggesting they were light limited. In contrast, A. corniculatum growth did not significantly differ between CO2 treatments. However, it had on average 36% greater growth under seawater salinity compared to hypersaline conditions. Avicennia marina seedlings were not affected by salinity. From these results, we suggest that although CO2 and salinity are not universal drivers determining saltmarsh-mangrove boundaries, it is likely that rising atmospheric CO2 concentration and reduced salinity associated with sea level rise will enhance the establishment success of mangrove seedlings in saltmarshes, which may facilitate mangrove encroachment in the future.

Digital plant pathology: a foundation and guide to modern agriculture.

Over the last 20 years, researchers in the field of digital plant pathology have chased the goal to implement sensors, machine learning and new technologies into knowledge-based methods for plant phenotyping and plant protection. However, the application of swiftly developing technologies has posed many challenges. Greenhouse and field applications are complex and differ in their study design requirements. Selecting a sensor type (e.g., thermography or hyperspectral imaging), sensor platform (e.g., rovers, unmanned aerial vehicles, or satellites), and the problem-specific spatial and temporal scale adds to the challenge as all pathosystems are unique and differ in their interactions and symptoms, or lack thereof. Adding host-pathogen-environment interactions across time and space increases the complexity even further. Large data sets are necessary to enable a deeper understanding of these interactions. Therefore, modern machine learning methods are developed to realize the fast data analysis of such complex data sets. This reduces not only human effort but also enables an objective data perusal. Especially deep learning approaches show a high potential to identify probable cohesive parameters during plant-pathogen-environment interactions. Unfortunately, the performance and reliability of developed methods are often doubted by the potential user. Gaining their trust is thus needed for real field applications. Linking biological causes to machine learning features and a clear communication, even for non-experts of such results, is a crucial task that will bridge the gap between theory and praxis of a newly developed application. Therefore, we suggest a global connection of experts and data as the basis for defining a common and goal-oriented research roadmap. Such high interconnectivity will likely increase the chances of swift, successful progress in research and practice. A coordination within international excellence clusters will be useful to reduce redundancy of research while supporting the creation and progress of complementary research. With this review, we would like to discuss past research, achievements, as well as recurring and new challenges. Having such a retrospect available, we will attempt to reveal future challenges and provide a possible direction elevating the next decade of research in digital plant pathology.

Urban stormwater run-off promotes compression of saltmarshes by freshwater plants and mangrove forests.

Subtropical and temperate coastal saltmarsh of Australia is listed as an endangered ecological community under the Commonwealth Environment Protection and Biodiversity Conservation Act (EPBC Act). Saltmarshes are under threat from sea level rise, landward migration of mangroves, and in urban regions from habitat loss, input of litter, nutrients, and other contaminants. In urbanised catchments, saltmarsh areas receive nutrient-enriched and pollutant-contaminated run-off, such as heavy metals, through the stormwater system. This study aimed to investigate the impact of urban stormwater on saltmarsh and mangrove species composition and distribution. To test the effect of stormwater run-off in urbanised catchments on saltmarsh communities, we analysed the soil for pollutant elements, salinity and nutrient concentration and recorded vegetation composition at eight sites in the Sydney region, Australia. We found that elevated total nitrogen (>0.4 wt%) and reduced salinity of the soil downslope of stormwater outlets facilitates establishment of exotic plants and might promote migration of mangroves into saltmarshes, resulting in a squeezing effect on the distribution of saltmarsh vegetation. Saltmarsh cover was significantly lower below stormwater outlets and exotic plant cover increased significantly with sediment calcium concentrations above 8840 mg/kg, which are associated with stormwater run-off. However, this effect was found to be strongest in highly industrialised areas compared to residential areas. Understanding the impact of pollutants on coastal wetlands will improve management strategies for the conservation of this important endangered ecological community.