Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales.

Behavioral health support and online peer communities: international experiences.

Online peer support communities play an important part in many people's experience of healthcare. They can be particularly significant in behavioral health/mental health due to the difficulties that people may experience in accessing face to face care for these conditions. There is considerable diversity of practice in service management, target group, and moderation practices of online peer support communities. People using the communities also appear to have diverse aims and experiences. This heterogeneity contributes to a relative lack of data about the value and effectiveness of online peer support in behavioral health, although there is significant research into some aspects of these communities. The digital behavioral health service Big White Wall was launched in the UK in 2007, and in the US in 2015, and is focused on delivering moderated peer support. There are considerable differences in health systems between the two countries, and this has been reflected in different experiences of implementation. The value of online peer support could be maximized if systemic challenges to implementation and adoption were addressed more effectively.

Soft tissue 'mallet' injury to the hallux.

We describe a case of a delayed presentation of a traumatic soft tissue mallet injury to the distal phalanx of the hallux in a teenager. Reports of this rare injury are sparse and there is no consensus in their treatment. This injury was treated with open repair of the tendon using a Mitek suture anchor, and stabilization with a 1.2-mm K-wire and extension splinting for 8 weeks. Following this treatment, she regained full power and a range of movement compared with the contralateral side, and achieved full function. We advocate surgical reconstruction of these injuries with suture anchors and stabilization of the interphalangeal joint.

Online groups and patient forums.

Online mental health support forums are becoming increasingly popular and there is evidence that they are useful: particularly for providing anonymous support and filling information gaps. However, there are also very real concerns about negative outcomes for users. One online mental health service, Big White Wall, manages these risks and supports its members through the provision of 24 hour professional moderation. Comparison of Big White Wall's member population with the population of one London borough shows a diverse user group, but members are more likely to be female, and aged 25 to 34, or unemployed.