Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Coping with multiple enemies - the evolution of resistance and host-parasitoid community structure

Recent work has shown that the evolution of Drosophila melanogaster resistance to attack by the parasitoid Asobara tabida is constrained by a trade-off with larval competitive ability. However, there are two very important questions that need to be answered. First, is this a general cost, or is it parasitoid specific? Second, does a selected increase in immune response against one parasitoid species result in a correlated change in resistance to other parasitoid species? The answers to both questions will influence the coevolutionary dynamics of these species, and also may have a previously unconsidered, yet important, influence on community structure.

Adapting to the effects of climate change on water supply reliability

This paper presents preliminary results from an assessment of the barriers to adaptation to water supply shortage in a case study catchment in south east England with multiple supply companies. The investigation applies a conceptual framework, which distinguishes between generic barriers affecting the ability of supply companies to make adaptation decisions, and specific barriers to the implementation of each option. The preliminary analysis suggests that whilst there is a widespread awareness of the challenge of climate change, and a conceptual understanding of the need for adaptation, some of the generic barriers that will affect detailed evaluations and actual adaptation decisions have yet to be approached. The analysis also shows that different individual adaptation options are assessed differently by different stakeholders, and that there are differences in the barriers to adoption between supply-side and demand-side measures. First, however, the paper develops the general conceptual framework for the characterisation of the barriers to adaptation used in the study.

A climate change risk analysis for world ecosystems

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenarios or weights to models. Instead, we consider distribution of outcomes within three sets of model runs grouped by the amount of global warming they simulate: <2°C (including simulations in which atmospheric composition is held constant, i.e., in which the only climate change is due to greenhouse gases already emitted), 2–3°C, and >3°C. High risk of forest loss is shown for Eurasia, eastern China, Canada, Central America, and Amazonia, with forest extensions into the Arctic and semiarid savannas; more frequent wildfire in Amazonia, the far north, and many semiarid regions; more runoff north of 50°N and in tropical Africa and northwestern South America; and less runoff in West Africa, Central America, southern Europe, and the eastern U.S. Substantially larger areas are affected for global warming >3°C than for <2°C; some features appear only at higher warming levels. A land carbon sink of ≈1 Pg of C per yr is simulated for the late 20th century, but for >3°C this sink converts to a carbon source during the 21st century (implying a positive climate feedback) in 44% of cases. The risks continue increasing over the following 200 years, even with atmospheric composition held constant.

Managing multiple markets: big firms and PFI contracts

The Private Finance Initiative (PFI) is frequently portrayed as a vehicle for change for the UK construction sector. Significant change in the working practices of construction companies is predicted as new business models based on whole-life value creation emerge. This paper shifts the focus of discussion from projected ideals and possible developments to the current situation. More specifically, it focuses on the challenges that large firms participating in both PFI and traditional markets face. The analysis focuses on the relations between business units and on day-to-day challenges to greater long-term commitment, through life-service provision and increased integration between construction and service provision. The paper offers insights into the effects of PFI on construction practice and their implications for theorizing on organizational and strategic change. It suggests abandoning a simplistic model of the centralized, homogenous firm and instead capturing the dynamics of decentralized, large firms working in multiple markets on a variety of projects. This would assist in the provision of more realistic and fruitful models of how to realize the PFI vision.

Strengthening the link between climate, hydrological and species distribution modeling to assess the impacts of climate change on freshwater biodiversity

To understand the resilience of aquatic ecosystems to environmental change, it is important to determine how multiple, related environmental factors, such as near-surface air temperature and river flow, will change during the next century. This study develops a novel methodology that combines statistical downscaling and fish species distribution modeling, to enhance the understanding of how global climate changes (modeled by global climate models at coarse-resolution) may affect local riverine fish diversity. The novelty of this work is the downscaling framework developed to provide suitable future projections of fish habitat descriptors, focusing particularly on the hydrology which has been rarely considered in previous studies. The proposed modeling framework was developed and tested in a major European system, the Adour-Garonne river basin (SW France, 116,000 km(2)), which covers distinct hydrological and thermal regions from the Pyrenees to the Atlantic coast. The simulations suggest that, by 2100, the mean annual stream flow is projected to decrease by approximately 15% and temperature to increase by approximately 1.2 °C, on average. As consequence, the majority of cool- and warm-water fish species is projected to expand their geographical range within the basin while the few cold-water species will experience a reduction in their distribution. The limitations and potential benefits of the proposed modeling approach are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Climate change and the emergence of new organizational landscapes

There is general agreement across the world that human-made climate change is a serious global problem,although there are still some sceptics who challenge this view. Research in organization studies on the topic is relatively new. Much of this research, however, is instrumental and managerialist in its focus on ‘win-win’ opportunities for business or its treatment of climate change as just another corporate social responsibility (CSR) exercise. In this paper, we suggest that climate change is not just an environmental problem requiring technical and managerial solutions; it is a political issue where a variety of organizations – state agencies, firms, industry associations, NGOs and multilateral organizations – engage in contestation as well as collaboration over the issue. We discuss the strategic, institutional and political economy dimensions of climate change and develop a socioeconomic regimes approach as a synthesis of these different theoretical perspectives. Given the urgency of the problem and the need for a rapid transition to a low-carbon economy, there is a pressing need for organization scholars to develop a better understanding of apathy and inertia in the face of the current crisis and to identify paths toward transformative change. The seven papers in this special issue address these areas of research and examine strategies, discourses, identities and practices in relation to climate change at multiple levels.

Importance of density-compensated temperature change for deep North Atlantic Ocean heat uptake

The efficiency with which the oceans take up heat has a significant influence on the rate of global warming. Warming of the ocean above 700 m over the past few decades has been well documented. However, most of the ocean lies below 700 m. Here we analyse observations of heat uptake into the deep North Atlantic. We find that the extratropical North Atlantic as a whole warmed by 1.45±0.5×1022 J between 1955 and 2005, but Lower North Atlantic Deep Water cooled, most likely as an adjustment from an early twentieth-century warm period. In contrast, the heat content of Upper North Atlantic Deep Water exhibited strong decadal variability. We demonstrate and quantify the importance of density-compensated temperature anomalies for long-term heat uptake into the deep North Atlantic. These anomalies form in the subpolar gyre and propagate equatorwards. High salinity in the subpolar gyre is a key requirement for this mechanism. In the past 50 years, suitable conditions have occurred only twice: first during the 1960s and again during the past decade. We conclude that heat uptake through density-compensated temperature anomalies will contribute to deep ocean heat uptake in the near term. In the longer term, the importance of this mechanism will be determined by competition between the multiple processes that influence subpolar gyre salinity in a changing climate.

The benefits of a compute cluster approach to high spatial resolution biodiversity richness modelling: projecting the impact of climate change on Mediterranean flora

High spatial resolution environmental data gives us a better understanding of the environmental factors affecting plant distributions at fine spatial scales. However, large environmental datasets dramatically increase compute times and output species model size stimulating the need for an alternative computing solution. Cluster computing offers such a solution, by allowing both multiple plant species Environmental Niche Models (ENMs) and individual tiles of high spatial resolution models to be computed concurrently on the same compute cluster. We apply our methodology to a case study of 4,209 species of Mediterranean flora (around 17% of species believed present in the biome). We demonstrate a 16 times speed-up of ENM computation time when 16 CPUs were used on the compute cluster. Our custom Java ‘Merge’ and ‘Downsize’ programs reduce ENM output files sizes by 94%. The median 0.98 test AUC score of species ENMs is aided by various species occurrence data filtering techniques. Finally, by calculating the percentage change of individual grid cell values, we map the projected percentages of plant species vulnerable to climate change in the Mediterranean region between 1950–2000 and 2020.

The use of land-sea warming contrast under climate change to improve impact metrics

A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.

Scale sensitivity of drivers of environmental change across Europe

The development of effective environmental management plans and policies requires a sound understanding of the driving forces involved in shaping and altering the structure and function of ecosystems. However, driving forces, especially anthropogenic ones, are defined and operate at multiple administrative levels, which do not always match ecological scales. This paper presents an innovative methodology of analysing drivers of change by developing a typology of scale sensitivity of drivers that classifies and describes the way they operate across multiple administrative levels. Scale sensitivity varies considerably among drivers, which can be classified into five broad categories depending on the response of ‘evenness’ and ‘intensity change’ when moving across administrative levels. Indirect drivers tend to show low scale sensitivity, whereas direct drivers show high scale sensitivity, as they operate in a non-linear way across the administrative scale. Thus policies addressing direct drivers of change, in particular, need to take scale into consideration during their formulation. Moreover, such policies must have a strong spatial focus, which can be achieved either by encouraging local–regional policy making or by introducing high flexibility in (inter)national policies to accommodate increased differentiation at lower administrative levels. High quality data is available for several drivers, however, the availability of consistent data at all levels for non-anthropogenic drivers is a major constraint to mapping and assessing their scale sensitivity. This lack of data may hinder effective policy making for environmental management, since it restricts the ability to fully account for scale sensitivity of natural drivers in policy design.

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.

What (science for) adaptation to climate change in Colombian agriculture? A commentary on “A way forward on adaptation to climate change in Colombian agriculture: perspectives towards 2050” by J. Ramirez-Villegas, M. Salazar, A. Jarvis, C. E. Navarro-Valcines.

Climate change is putting Colombian agriculture under significant stress and, if no adaptation is made, the latter will be severely impacted during the next decades. Ramirez-Villegas et al. (2012) set out a government-led, top-down, techno-scientific proposal for a way forward by which Colombian agriculture could adapt to climate change. However, this proposal largely overlooks the root causes of vulnerability of Colombian agriculture, and of smallholders in particular. I discuss some of the hidden assumptions underpinning this proposal and of the arguments employed by Ramirez-Villegas et al., based on existing literature on Colombian agriculture and the wider scientific debate on adaptation to climate change. While technical measures may play an important role in the adaptation of Colombian agriculture to climate change, I question whether the actions listed in the proposal alone and specifically for smallholders, truly represent priority issues. I suggest that by i) looking at vulnerability before adaptation, ii) contextualising climate change as one of multiple exposures, and iii) truly putting smallholders at the centre of adaptation, i.e. to learn about and with them, different and perhaps more urgent priorities for action can be identified. Ultimately, I argue that what is at stake is not only a list of adaptation measures but, more importantly, the scientific approach from which priorities for action are identified. In this respect, I propose that transformative rather than technical fix adaptation represents a better approach for Colombian agriculture and smallholders in particular, in the face of climate change.

The role of oceans and sea ice in abrupt transitions between multiple climate states

The coupled climate dynamics underlying large, rapid, and potentially irreversible changes in ice cover are studied. A global atmosphere–ocean–sea ice general circulation model with idealized aquaplanet geometry is forced by gradual multi-millennial variations in solar luminosity. The model traverses a hysteresis loop between warm ice-free conditions and cold glacial conditions in response to ±5 W m−2 variations in global, annual-mean insolation. Comparison of several model configurations confirms the importance of polar ocean processes in setting the sensitivity and time scales of the transitions. A “sawtooth” character is found with faster warming and slower cooling, reflecting the opposing effects of surface heating and cooling on upper-ocean buoyancy and, thus, effective heat capacity. The transition from a glacial to warm, equable climate occurs in about 200 years. In contrast to the “freshwater hosing” scenario, transitions are driven by radiative forcing and sea ice feedbacks. The ocean circulation, and notably the meridional overturning circulation (MOC), does not drive the climate change. The MOC (and associated heat transport) collapses poleward of the advancing ice edge, but this is a purely passive response to cooling and ice expansion. The MOC does, however, play a key role in setting the time scales of the transition and contributes to the asymmetry between warming and cooling.

Scale sensitivity of drivers of environmental change across Europe

The development of effective environmental management plans and policies requires a sound understanding of the driving forces involved in shaping and altering the structure and function of ecosystems. However, driving forces, especially anthropogenic ones, are defined and operate at multiple administrative levels, which do not always match ecological scales. This paper presents an innovative methodology of analysing drivers of change by developing a typology of scale sensitivity of drivers that classifies and describes the way they operate across multiple administrative levels. Scale sensitivity varies considerably among drivers, which can be classified into five broad categories depending on the response of ‘evenness’ and ‘intensity change’ when moving across administrative levels. Indirect drivers tend to show low scale sensitivity, whereas direct drivers show high scale sensitivity, as they operate in a non-linear way across the administrative scale. Thus policies addressing direct drivers of change, in particular, need to take scale into consideration during their formulation. Moreover, such policies must have a strong spatial focus, which can be achieved either by encouraging local–regional policy making or by introducing high flexibility in (inter)national policies to accommodate increased differentiation at lower administrative levels. High quality data is available for several drivers, however, the availability of consistent data at all levels for non-anthropogenic drivers is a major constraint to mapping and assessing their scale sensitivity. This lack of data may hinder effective policy making for environmental management, since it restricts the ability to fully account for scale sensitivity of natural drivers in policy design.