3,567 research outputs found

    Tasmanian Midlands options to improve biodiversity governance arrangements

    Get PDF
    Conserving landscapes rich in biodiversity requires long-term planning and understanding of how social and ecological systems co-evolve. How such landscapes are governed (that is, the structures and processes that determine who has influence, who decides, and how decision-makers are held accountable) is pivotal to the long-term conservation of this biodiversity. Being able to govern across diverse landscapes, like the Tasmanian Midlands, where there are multiple landholders and multiple values, is a challenging task. Governance can improve biodiversity outcomes indirectly by enabling decision-making and management actions that are more responsive to environmental and social conditions. Better biodiversity outcomes could mean improving the extent and/or condition of biodiversity values or reducing the threat to those values. For example, this could be an increase in extent and improvement in condition of lowland native grasslands. Better outcomes might also include a decline in threats from invasive species or a land use mix that is more favourable to conservation. The process to generate the two governance options presented in this document is pictured on the following page. The research team developed two initial proposals for governance arrangements through an analysis of findings from key informant interviews, complemented by a review of the literature to identify whether best practice case studies elsewhere could offer innovative ways forward. The two proposed options were then discussed at three focus groups: one that prioritised input from Tasmanian Midlands landholders and their representative organisations; one focused on input from the Tasmanian state government staff; and one that focused on input from Australian Government staff

    Reducing High Flows and Sediment Loading Through Increased Water Storage in an Agricultural Watershed of the Upper Midwest, USA

    Get PDF
    Climate change, land clearing, and artificial drainage have increased the Minnesota River Basin’s (MRB) stream flows, enhancing erosion of channel banks and bluffs. Accelerated erosion has increased sediment loads and sedimentation rates downstream. High flows could be reduced through increased water storage (e.g., wetlands or detention basins), but quantifying the effectiveness of such a strategy remains a challenge. We used the Soil and Water Assessment Tool (SWAT) to simulate changes in river discharge from various water retention site (WRS) implementation scenarios in the Le Sueur watershed, a tributary basin to the MRB. We also show how high flow attenuation can address turbidity issues by quantifying the impact on near-channel sediment loading in the watershed’s incised reaches. WRS placement in the watershed, hydraulic conductivity (K), and design depth were varied across 135 simulations. The dominant control on site performance is K, with greater flow reductions allowed by higher seepage rates and less frequent overflowing. Deeper design depths enhance flow reductions from sites with low K values. Differences between WRS placement scenarios are slight, suggesting that site placement is not a first-order control on overall performance in this watershed. Flow reductions exhibit power-law scaling with exceedance probability, enabling us to create generalized relationships between WRS extent and flow reductions that accurately reproduce our SWAT results and allow for more rapid evaluation of future scenarios. Overall, we show that increasing water storage within the Le Sueur watershed can be an effective management option for high flow and sediment load reduction

    Emergence of heat extremes attributable to anthropogenic influences

    Get PDF
    Climate scientists have demonstrated that a substantial fraction of the probability of numerous recent extreme events may be attributed to human-induced climate change. However, it is likely that for temperature extremes occurring over previous decades a fraction of their probability was attributable to anthropogenic influences. We identify the first record-breaking warm summers and years for which a discernible contribution can be attributed to human influence. We find a significant human contribution to the probability of record-breaking global temperature events as early as the 1930s. Since then, all the last 16 record-breaking hot years globally had an anthropogenic contribution to their probability of occurrence. Aerosol-induced cooling delays the timing of a significant human contribution to record-breaking events in some regions. Without human-induced climate change recent hot summers and years would be very unlikely to have occurred.111411Ysciescopu

    The association between green space and cause-specific mortality in urban New Zealand: an ecological analysis of green space utility

    Get PDF
    <b>Background:</b> There is mounting international evidence that exposure to green environments is associated with health benefits, including lower mortality rates. Consequently, it has been suggested that the uneven distribution of such environments may contribute to health inequalities. Possible causative mechanisms behind the green space and health relationship include the provision of physical activity opportunities, facilitation of social contact and the restorative effects of nature. In the New Zealand context we investigated whether there was a socioeconomic gradient in green space exposure and whether green space exposure was associated with cause-specific mortality (cardiovascular disease and lung cancer). We subsequently asked what is the mechanism(s) by which green space availability may influence mortality outcomes, by contrasting health associations for different types of green space. <b>Methods:</b> This was an observational study on a population of 1,546,405 living in 1009 small urban areas in New Zealand. A neighbourhood-level classification was developed to distinguish between usable (i.e., visitable) and non-usable green space (i.e., visible but not visitable) in the urban areas. Negative binomial regression models were fitted to examine the association between quartiles of area-level green space availability and risk of mortality from cardiovascular disease (n = 9,484; 1996 - 2005) and from lung cancer (n = 2,603; 1996 - 2005), after control for age, sex, socio-economic deprivation, smoking, air pollution and population density. <b>Results:</b> Deprived neighbourhoods were relatively disadvantaged in total green space availability (11% less total green space for a one standard deviation increase in NZDep2001 deprivation score, p < 0.001), but had marginally more usable green space (2% more for a one standard deviation increase in deprivation score, p = 0.002). No significant associations between usable or total green space and mortality were observed after adjustment for confounders. <b>Conclusion</b> Contrary to expectations we found no evidence that green space influenced cardiovascular disease mortality in New Zealand, suggesting that green space and health relationships may vary according to national, societal or environmental context. Hence we were unable to infer the mechanism in the relationship. Our inability to adjust for individual-level factors with a significant influence on cardiovascular disease and lung cancer mortality risk (e.g., diet and alcohol consumption) will have limited the ability of the analyses to detect green space effects, if present. Additionally, green space variation may have lesser relevance for health in New Zealand because green space is generally more abundant and there is less social and spatial variation in its availability than found in other contexts

    An evaluation of strategies used by the Landscapes and Policy Hub to achieve interdisciplinary and transdisciplinary research

    Get PDF
    The report presents an evaluation of the Landscapes and Policy Hub's approach to interdisciplinary and transdisciplinary research. The hub was a national, four year, $15 million collaborative research program. The focus of the evaluation was for researchers to reflect on the effectiveness of strategies used by the hub to facilitate interdisciplinarity (where researchers from different disciplines work together to solve problems) and transdisciplinarity (where researchers from different disciplines work in partnership with research users to solve problems). The evaluation was commissioned in the final phase of the hub’s life in the interests of improving performance of future interdisciplinary and transdisciplinary research. It was based on a number of strategies that had been implemented by the hub to encourage and facilitate interdisciplinary research occurring in partnership with research users. The aim of the evaluation was to improve performance of future interdisciplinary and transdisciplinary research. Six recommendations are presented

    Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series.

    Get PDF
    Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused cognitive therapy treatment approach (MAPP; Mood Action Psychology Programme) targeting a driver of mood instability, and apply these measurement methods in a non-concurrent multiple baseline design case series of 14 patients with bipolar disorder. Weekly mood monitoring and treatment target data improved for the whole sample combined. Time-series analyses of daily mood data, sampled remotely (mobile phone/Internet) for 28 days pre- and post-treatment, demonstrated improvements in individuals' mood stability for 11 of 14 patients. Thus the findings offer preliminary support for a new imagery-focused treatment approach. They also indicate a step in treatment innovation without the requirement for trials in illness episodes or relapse prevention. Importantly, daily measurement offers a description of mood instability at the individual patient level in a clinically meaningful time frame. This costly, chronic and disabling mental illness demands innovation in both treatment approaches (whether pharmacological or psychological) and measurement tool: this work indicates that daily measurements can be used to detect improvement in individual mood stability for treatment innovation (MAPP)

    Circulating Apolipoprotein E Concentration and Cardiovascular Disease Risk: Meta-analysis of Results from Three Studies

    Get PDF
    Background: The association of APOE genotype with circulating apolipoprotein E (ApoE) concentration and cardiovascular disease (CVD) risk is well established. However, the relationship of circulating ApoE concentration and CVD has received little attention. Methods and Findings: To address this, we measured circulating ApoE concentration in 9,587 individuals (with 1,413 CVD events) from three studies with incident CVD events: two population-based studies, the English Longitudinal Study of Ageing (ELSA) and the men-only Northwick Park Heart Study II (NPHSII), and a nested sub-study of the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT). We examined the association of circulating ApoE with cardiovascular risk factors in the two population-based studies (ELSA and NPHSII) and the relationship between ApoE concentration and coronary heart disease and stroke in all three studies. Analyses were carried out within study, and, where appropriate, pooled effect estimates were derived using meta-analysis. In the population-based samples, circulating ApoE was associated with systolic blood pressure (correlation coefficient 0.08, p < 0.001, in both ELSA and NPHSII), total cholesterol (correlation coefficient 0.46 and 0.34 in ELSA and NPHSII, respectively; both p < 0.001), low-density lipoprotein cholesterol (correlation coefficient 0.30 and 0.14, respectively; both p < 0.001), high-density lipoprotein (correlation coefficient 0.16 and ?0.14, respectively; both p < 0.001), and triglycerides (correlation coefficient 0.43 and 0.46, respectivly; both p < 0.001). In NPHSII, ApoE concentration was additionally associated with apolipoprotein B (correlation coefficient 0.13, p = 0.001) and lipoprotein(a) (correlation coefficient ?0.11, p < 0.001). In the pooled analysis of ASCOT, ELSA, and NPHSII, there was no association of ApoE with CVD events; the odds ratio (OR) for CVD events per 1-standard-deviation higher ApoE concentration was 1.02 (95% CI 0.96, 1.09). After adjustment for cardiovascular risk factors, the OR for CVD per 1-standard-deviation higher ApoE concentration was 0.97 (95% CI 0.82, 1.15). Limitations of these analyses include a polyclonal method of ApoE measurement, rather than isoform-specific measurement, a moderate sample size (although larger than any other study to our knowledge and with a long lag between ApoE measures), and CVD events that may attenuate an effect. Conclusions: In the largest study to date on this question, we found no evidence of an association of circulating ApoE concentration with CVD events. The established association of APOE genotype with CVD events may be explained by isoform-specific functions as well as other mechanisms, rather than circulating concentrations of ApoE

    A dynamic network approach for the study of human phenotypes

    Get PDF
    The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure
    corecore