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Urban Green Infrastructure (GI) provides multiple benefits to city inhabitants and can be an important component in nature-based solutions (NBS), but the ecosystem services that underpin those benefits are inconsistently quantified in the literature. There remain substantial knowledge gaps about the level of service supported by less studied GI types, e.g. cemeteries, or less-studied ecosystem services, e.g. noise mitigation. Decision-makers and planners in cities often face conflicting or incomplete information on the effectiveness of GI, particularly on their ability to provide a suite of co-benefits. Here, we describe a feature-based typology of GI which combines elements of land cover, land use and both ecological and social function. It is consistent with user requirements on mapping, and with the needs of models which can conduct more detailed ecosystem service assessments which can guide NBS design. We provide an evidence synthesis based on published literature, which scores the ability of each GI type to deliver a suite of ecosystem services. In the multivariate analysis of the typology scores, the main axis of variation differentiates between constructed (or hybrid) GI types designed primarily for water flow management (delivering relatively few services) and more natural green GI with trees, or blue GI such as lakes and the sea, which deliver a more multi-functional set of regulating services. The most multi-functional GI on this axis also score highest for biodiversity. The second element of variation separates those GI which support very few cultural services and those which score highly in enabling physical wellbeing and social interaction and, to a lesser extent, restoring capacities. Together the typology and multi-functionality matrix provide a much needed assessment for less studied GI types, and allow planners and decision-makers to make a-priori assessments of the relative ability of different GI as part of NBS to address urban challenges.

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Translocation has been used to conserve imperiled fishes and create new fisheries. One species for which translocation has played a significant role is the Sacramento Perch Archoplites interruptus. Extirpated from its native range, the Sacramento Perch has been introduced throughout California and Nevada through multiple translocation events, though historical records are incomplete. Recent assessments of eight previously uncharacterized Sacramento Perch populations have prompted reevaluation of range-wide population structure to inform a genetic management plan for long-term resiliency of this species. We examined Sacramento Perch genetic diversity and population structure across the current range of the species using 12 microsatellite markers. We analyzed samples from the eight uncharacterized populations and seven populations previously studied by Schwartz and May (2008). Bayesian clustering supported two distinct clusters of Sacramento Perch herein designated as A and B. Within these two clusters we detected hierarchical substructure, likely due to genetic drift after population founding. Genetic differentiation among populations within the same cluster was relatively low (FST = 0.023–0.176), while differentiation among populations from different clusters was higher (FST = 0.190–0.320). The existence of two strongly divergent genetic clusters in Sacramento Perch suggests two distinct translocation sources, and we recommend that these clusters be treated as genetic management units (GMUs). The B GMU populations had fairly low levels of genetic diversity relative to the A GMU populations. All populations showed evidence of past bottlenecks, and most had effective population sizes placing them at risk for inbreeding depression. Human-facilitated gene flow is recommended to prevent further genetic diversity loss. Due to uncertainty surrounding Sacramento Perch translocation history and strong levels of divergence between the two GMUs, translocati

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Engagement with nature is an important part of many people’s lives, and the health and wellbeing benefits of nature–based activities are becoming increasingly recognised across disciplines from city planning to medicine. Despite this, urbanisation, challenges of modern life and environmental degradation are leading to a reduction in both the quantity and the quality of nature experiences. Nature–based health interventions (NBIs) can facilitate behavioural change through a somewhat structured promotion of nature–based experiences and, in doing so, promote improved physical, mental and social health and wellbeing. We conducted a Delphi expert elicitation process with 19 experts from seven countries (all named authors on this paper) to identify the different forms that such interventions take, the potential health outcomes and the target beneficiaries. In total, 27 NBIs were identified, aiming to prevent illness, promote wellbeing and treat specific physical, mental or social health and wellbeing conditions. These interventions were broadly categorized into those that change the environment in which people live, work, learn, recreate or heal (for example, the provision of gardens in hospitals or parks in cities) and those that change behaviour (for example, engaging people through organized programmes or other activities). We also noted the range of factors (such as socioeconomic variation) that will inevitably influence the extent to which these interventions succeed. We conclude with a call for research to identify the drivers influencing the effectiveness of NBIs in enhancing health and wellbeing.

© 2019 Sports Medicine Australia Objectives: To examine the influence of maturation and its interaction with playing position upon physical match performances in U15 footballers from a national federation. Design: Observational study. Methods: 278 male outfield players competing in a national tournament were assessed for somatic maturity and match physical performances according to playing position. Stature, sitting height, and body mass were measured and entered into an algorithm to estimate the age at peak height velocity (APHV). Players match movements were recorded by Global Positioning System devices (10 Hz), to determine peak speed, and total- (TD), low-speed running (LSR; ≤13.0 km h−1), high-speed running (HSR; 13.1–16.0 km h−1), very high-speed running (VHSR; 16.1–20.0 km h−1) and sprint distances (SPR; >20.0 km h−1) expressed relative to match exposure (m min−1). Results: Linear-mixed models using log transformed response variables revealed a significant contribution of estimated APHV upon TD (1.01; 95% CI: 0.99–1.02 m·min−1; p < 0.001), HSR (1.05; 95% CI: 0.98–1.13 m min−1; p < 0.001) and VHSR (1.07; 95% CI: 1.00–1.14 m min−1; p = 0.047). An increase by one year in APHV was associated with an increase of 0.6, 5.4 and 6.9% in TD, HSR and VHSR respectively. No effects of APHV were observed for LSR, SPR, and peak speed. Further, no APHV effects were observed relative to players’ field position. Conclusions: Later maturing players covered substantially more higher-intensity (HSR and VHSR) running in matches, irrespective of playing position. The greater match intensity of later maturing players may inform talent identification and athletic development processes within a national federation.

© 2017 Human Kinetics, Inc. Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance.

Background: Many studies suggest that exposure to natural environments ('greenspace') enhances human health and wellbeing. Benefits potentially arise via several mechanisms including stress reduction, opportunity and motivation for physical activity, and reduced air pollution exposure. However, the evidence is mixed and sometimes inconclusive. One explanation may be that "greenspace" is typically treated as a homogenous environment type. However, recent research has revealed that different types and qualities of natural environments may influence health and wellbeing to different extents. Methods: This ecological study explores this issue further using data on land cover type, bird species richness, water quality and protected or designated status to create small-area environmental indicators across Great Britain. Associations between these indicators and age/sex standardised prevalence of both good and bad health from the 2011 Census were assessed using linear regression models. Models were adjusted for indicators of socio-economic deprivation and rurality, and also investigated effect modification by these contextual characteristics. Results: Positive associations were observed between good health prevalence and the density of the greenspace types, "broadleaf woodland", "arable and horticulture", "improved grassland", "saltwater" and "coastal", after adjusting for potential confounders. Inverse associations with bad health prevalence were observed for the same greenspace types, with the exception of "saltwater". Land cover diversity and density of protected/designated areas were also associated with good and bad health in the predicted manner. Bird species richness (an indicator of local biodiversity) was only associated with good health prevalence. Surface water quality, an indicator of general local environmental condition, was associated with good and bad health prevalence contrary to the manner expected, with poorer water quality associated with better populat