Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

Modelling and assessment of South African elephant Loxodonta africana population persistence

The use of a quantitative population growth model to investigate the persistence of South African elephant populations is explored. The model provides quantitative assessments of population persistence and confidence intervals for estimated parameters based purely on population size estimates. The analysis supports the view that most of the larger populations in the region are secure. This view is further supported by a lack of density dependent effects in most of the recovering populations and the high population rates of increase observed. This predominantly positive prognosis is in contrast with that emerging from most of the rest of the African continent where the populations are under greater threat because of habitat restriction and direct human conflict. This preliminary assessment of elephant population persistence suggests that “viable” populations may lie between 400 and 6000 individuals. Although not inconsistent with information-greedy genetic and demographic models, the relationship between population growth versus genetic and demographic models should be further investigated. The implementation of a metapopulation management strategy towards these smaller populations is advocated. In addition, as all of the populations included in this analysis have been afforded some degree of protection since the 1920s, continued protection would be a prerequisite for their continued survival.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Beyond ‘just’ flood risk management: the potential for—and limits to—alleviating flood disadvantage

Regional Environmental Change - The threat of flooding poses a considerable challenge for justice. Not only are more citizens becoming exposed to risk, but they are expected to play increasingly...     

Variation in perception of environmental change in nine Solomon Islands communities: implications for securing fairness in community-based adaptation

Community-based approaches are pursued in recognition of the need for place-based responses to environmental change that integrate local understandings of risk and vulnerability. Yet the potential for fair adaptation is intimately linked to how variations in perceptions of environmental change and risk are treated. There is, however, little empirical evidence of the extent and nature of variations in risk perception in and between multiple community settings. Here, we rely on data from 231 semi-structured interviews conducted in nine communities in Western Province, Solomon Islands, to statistically model different perceptions of risk and change within and between communities. Overall, people were found to be less likely to perceive environmental changes in the marine environment than they were for terrestrial systems. The distance to the nearest market town (which may be a proxy for exposure to commercial logging and degree of involvement with the market economy), and gender had the greatest overall statistical effects on perceptions of risk. Yet, we also find that significant environmental change is underreported in communities, while variations in perception are not always easily related to commonly assumed fault lines of vulnerability. The findings suggest that there is an urgent need for methods that engage with the drivers of perceptions as part of community-based approaches. In particular, it is important to explicitly account for place, complexity and diversity of environmental risk perceptions, and we reinforce calls to engage seriously with underlying questions of power, culture, identity and practice that influence adaptive capacity and risk perception.

     

The socio-economic vulnerability of the Australian east coast grazing sector to the impacts of climate change

Regional Environmental Change - Research that projects biophysical changes under climate change is more advanced than research that projects socio-economic changes. There is a need in adaptation...     

Designing the next generation of climate adaptation research for development

Adaptation research has changed significantly in recent years as funders and researchers seek to encourage greater impact, ensure value for money and promote interdisciplinarity across the natural and social sciences. While these developments are inherently positive, they also bring fresh challenges. With this in mind, this paper presents an agenda for the next generation of climate adaptation research for development. The agenda is based on insights from a dialogue session held at the 2016 Adaptation Futures conference as well as drawing on the collective experience of the authors. We propose five key areas that need to be changed in order to meet the needs of future adaptation research, namely: increasing transparency and consultation in research design; encouraging innovation in the design and delivery of adaptation research programmes; demonstrating impact on the ground; addressing incentive structures; and promoting more effective brokering, knowledge management and learning. As new international funding initiatives start to take shape, we underscore the importance of learning from past experiences and scaling-up of successful innovations in research funding models.

     

Socio-environmental consideration of phosphorus flows in the urban sanitation chain of contrasting cities

Understanding how cities can transform organic waste into a valuable resource is critical to urban sustainability. The capture and recycling of phosphorus (P), and other essential nutrients, from human excreta is particularly important as an alternative organic fertilizer source for agriculture. However, the complex set of socio-environmental factors influencing urban human excreta management is not yet sufficiently integrated into sustainable P research. Here, we synthesize information about the pathways P can take through urban sanitation systems along with barriers and facilitators to P recycling across cities. We examine five case study cities by using a sanitation chains approach: Accra, Ghana; Buenos Aires, Argentina; Beijing, China; Baltimore, USA; and London, England. Our cross-city comparison shows that London and Baltimore recycle a larger percentage of P from human excreta back to agricultural lands than other cities, and that there is a large diversity in socio-environmental factors that affect the patterns of recycling observed across cities. Our research highlights conditions that may be “necessary but not sufficient” for P recycling, including access to capital resources. Path dependencies of large sanitation infrastructure investments in the Global North contrast with rapidly urbanizing cities in the Global South, which present opportunities for alternative sanitation development pathways. Understanding such city-specific social and environmental barriers to P recycling options could help address multiple interacting societal objectives related to sanitation and provide options for satisfying global agricultural nutrient demand.

     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...