Abstract Innovationecosystems can be constructed around any subject matter. We choose here the topic of gender, which we examine as a component of innovation success. Most analyses of innovation systems tend to assume gender-neutral position with regard to identity and roles of participating actors and their activities. However, real-life innovations can often result in different quality of outcomes for women and men; the innovation potential of highly trained women remains unrealised; and the recent socioeconomic empowerment of women as driver of market needs continues to be ignored. Drawing on latest research evidence from studies of gender issues in science, we show how innovation systems can benefit from adopting more gender sensitive approaches, which recognise the role gender plays in shaping knowledge and market activities. We propose four scenarios for constructing gender sensitive innovationecosystems based on different gender dynamics that combine scientific understanding of sex and gender differences with improved engagement of women in innovation process, enabled through participatory methods and open and inclusive innovation practices.
Figure 2 emphasises the need for blurred boundaries between the triple helix partici- pants to support both exploration and exploitation in the offshore wind innovation eco- system. The important issues are flexible alignment of the regulatory framework for support of both arms ’ length and collaborative practices. Next, a focus of the helixes on timing, transparency and open collaboration practices is needed. The complementarity of SME innovationdynamics can be used in conjunction with university research and educational collaboration to join forces to enable innovation in the offshore ecosystem. These issues are, to some extent, ambiguous, and to some extent, they overlap. Hereby, the ambidextrous capacity of the innovation ecosystem is stressed for a more thorough understanding and insight for policy, educational and research initiatives to support the overall aim.
ecosystem has now become valuable currency as clini- cal evidence becomes an increasingly important mar- ket driver for new diagnostic business models that use next generation sequencing and other high throughput technologies for diagnostic medicine. Reimbursement, patent, and market landscape dynamics for in vitro diagnostic kits will continually erode the proprietary value of an assay kit . There is a trend toward open dissemination of knowledge supporting biomarkers validation and peer review of biomarkers used in the course of clinical trial stratification and in the treat- ment decision making process itself . These trends further the commoditization of biomarkers as content (as demonstrated by the recent approval of Founda- tion 1 CDx, Table 1), There are a number of biobank networks, registries, and data ecosystems emerging in oncology that are aggregating clinical cases and –omic data at population scale. Some are primarily academic consortia, others are mostly supported by private com- panies. Cutting-edge computational approaches like machine learning can be applied to mine and infer criti- cal information from real clinical cases where clinical and outcome annotation are coupled with sequencing data.
This paper provides the discussion regarding the nature, origins and diversity of innovationecosystems with particular emphasis on the context of the emerging economies and “smart specialisation” paradigm of regional development. Bridging the gap between the research economy and commercial economy (“Valley of Death”) remains one of the key concerns of the mature and institutionalised innovationecosystems. However, many of the emerging innovationecosystems still suffer from underdeveloped institutional frameworks and fragmented ties of actors, which is a more pronounced challenge than “Valley of Death”. It is important to take into consideration the specific needs of different innovationecosystems in the context of the current EU innovation and regional policies (recently synergised under “smart specialization”). The development of sustainable innovation ecosystem requires a different mentality than the traditional institutional-regulatory approach adopted in the context of national innovation systems. It means the search for delicate balance between the supply- side and demand-side interventions, public and private, openness and ownership, long-term and short-term perspectives, quality of elements and their relationships, adequate policy actions and smooth functioning of the “invisible hand”. The emerging innovationecosystems need to complement their entrepreneurial profiles with stronger institutional frameworks and innovation support mechanisms, whereas the mature institutionalised innovationecosystems should not over-rely on institutional, supply-side solutions, but strengthen the entrepreneurial culture that is even more critical to innovation success.
Acknowledgements. Parts of this study were financially supported by the German Research Foundation (grant no. LO 1150/9-1) and conducted within the LandScales project (“Connecting processes and structures driving the landscape carbon dynamics over scales”) financed by the Leibniz Association within the Joint Initiative for Research and Innovation (BMBF) and (partially) carried out within the SMART Joint Doctorate (Science for the MAnagement of Rivers and their Tidal systems) funded with the support of the Erasmus Mundus program of the European Union and the Swiss National Science Foundation (grant no. PA00P2_142041). The development and production of the chambers with built-in CO 2 loggers (data set C) was supported by the Swedish Research Council VR. Funding for an initial workshop was carried out by the IGB cross-cutting research domain “Aquatic Boundaries and Linkages”. We gratefully acknowledge the financial support of German Academic Exchange Service (DAAD) (Sustainable water management Program (NAWAM), grant no. A/12/91768). We thank Simone Langhans for her fruitful input, which shaped the core idea of the presented study. Finally, we thank the two anony- mous reviewers for constructive input that improved the manuscript. Edited by: H. Niemann
environment based on well-defined, if sometimes questionable, assumptions. As a result of many national and international research initiatives, a broad range of nitrogen models has been developed commensurate with the different aspects of nitrogen pollution (such as nitrogen leaching from forests, grassland and arable dominated systems, soil and stream water acidification, within-river and -lake eutrophication and gaseous emissions) and data availability. This paper summarises the results of the science in this and in a previous Special Issue of Hydrology and Earth System Sciences (Volume 6, Issue no. 3, 2002), dedicated to assessing nitrogen dynamics in catchments across Europe within a modelling framework. This second volume is focused on the continuing development and testing of INCA, a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (Whitehead et al., 1998a,b; Wade et al., 2002a) in the context of a major initiative dealing with the prediction and management of aquatic nitrogen pollution across Europe (Wade et al., 2002b). Also, the results of further modelled scenarios are reported, which quantify the likely impacts of deposition, climatic and land- use changes on the nitrogen dynamics in river systems and build on the first scenarios run for UK systems (Limbrick et al., 2000; Flynn et al., 2002; Jarvie et al., 2002; Skeffington, 2002). The initiative was originally sponsored by the European Union under the project Integrated Nitrogen Model for European Catchments, contract number EVK1- 1999-00011, and will continue as part of the EU 6th Framework Euro-limpacs Integrated Project, contract no. GOCE-CT-2003-505540 (www.eurolimpacs.ucl.ac.uk).
Building on such conceptual premises, evolutionary approaches advance two important propositions. First, the growth of knowledge is a path dependent process which develops along trajectories of technical and procedural understanding (Dosi, 1988; David, 2001). Second, the efficacy of new knowledge depends on the feedbacks generated by its application in relation to specific problems. Social understanding is central both for the accumulation and the recombination of knowledge. In turn, when the growth of knowledge spans different boundaries innovation (viz. effective problem solving) is characterised like a collective process that draws on and impinges on a variety of sources (Antonelli, 2001; Kogut and Zander, 2003). Let us now cast these themes in the analysis of medical innovation.
complex system behaviour have yet to be substantiated’; and (iii) it ‘offers no ready metrics’. Together, these limitations provide a context for the contribution of this study, which evaluates the role of public policy in pro- moting cooperation as a measurable outcome. Evalua- tion of innovation policies has been mainly conducted within the confines of mainstream theories of public support for innovation and, hence, has mainly been concerned with input and output additionalities. Yet focussing on innovation inputs and outputs means that we stay outside the ‘black box’ of innovation processes (OECD 2006). Conversely, broadening the theoretical underpinnings of evaluation studies to include evolu- tionary insights and systems perspectives on innovation enables more complete assessment of the impact of public measures on firms’ innovative behaviour (Buisseret et al. 1995; Georghiou and Clarysse 2006). In particular, cooperation potentially induced by inno- vation support programmes is a form of behavioural additionality (OECD 2006; Falk 2007; Wanzenbӧck et al. 2013). 2 This study contributes to this broader approach to the evaluation of innovation support poli- cies by analysing the same dataset as [Radicic et al. 2016, p. 1425] who report that ‘ for participants, the estimated effects of publicly funded innovation support programmes on SMEs in traditional manufacturing in- dustries are positive, typically increasing the probability of innovation and of its commercial success by around 15%’. In this study, we report that the innovation sup- port programmes investigated by [Radicic et al. 2016] give rise in addition to behavioural benefits in the form of ‘network or cooperation additionality’. In turn, in Section 3 below, we argue that by giving rise to more cooperation than there would otherwise be (i.e. in the no policy support counterfactual), innovation support programmes may contribute to the well-functioning of innovationecosystems and thus promote cooperative innovation performance in ways not accounted for in traditional evaluation studies. Accordingly, our main research question is whether public support measures
The reality in the widest sense of interaction and physics is represented within a delineated spatial unit of the atmosphere – vegetation cover – aera- tion zone – ground water chain by water transport processes (ŠÚTOR, ŠTEKAUEROVÁ 2000). Inﬁltration as the initial component and evapotranspiration as the ﬁnal component of water balance in the process of the water regime of soils are determined by the hydrophysical characteristics of soil (soil moisture retention line, hydraulic conductivity of soil, po- rosity, bulk density, weight volume) as well as by the transforming inﬂuence of the most important parameters of forest stand (tree species, stocking, canopy, phenophase, etc.) in the forest ecosystems.
scenario of known products, innovation strategies were focused on processes. However, for three reasons, the interest in product innovations is growing. Firstly, there is an increasing search for drop in fuels . Drop in fuels deliver a performance equal or close to that of con- ventional fuels (gasoline, diesel, or jet fuels). Thus, en- gine adaptation is not required and the existing transport and distribution infrastructure can be easily accessed. In this aspect, the available complementary as- sets could favor the drop in fuels instead of ethanol. Sec- ondly, the interest in biobased chemicals instead of biofuels has been growing. Some projects are dedicated to the production of chemicals and polymers: existing chemi- cals using new biobased routes and new products not cur- rently available in the petrochemical industry. The third factor is a combination of the two mentioned above. Prod- uct portfolio diversification allows for combining biofuels, which are high-volume and low-price products, with che- micals and specialties that tend to be lower-volume and higher-margin products. As a consequence, the importance of integrated biorefineries with multiple products has been increasing. These projects, compared to the dedicated production of biofuels, are still in the ini- tial stages of development but are seen as key to the future of the biobased economy . It must be remembered that product diversification can reinforce the environmen- tal performance of the biobased industry as well .
NaOH-I P fractions are generally considered to represent the more labile pools of soil organic P (Condron et al., 2005). This suggests that the quantity and turnover of organic P in soil may have been reduced following the cessation of grazing. Grazing animals play a very important role in the process of P cycling in pasture ecosystems since 95% of the P taken up by plants is returned to the soil in the form of feces and root residues, while only 25% of ingested P is commonly removed by transfer of animal excreta within the system (Haynes and Williams, 1993; Kemp et al., 2000). Simpson et al. (2012) investigated the relative solubility of soil P under contrasting mowing regimes (no mowing, clippings removed, clippings left) which had been maintained in a field trial for 15 years. In approximate terms, the regime where clippings were left was equivalent to grazing while no mowing would be equivalent the situation at Orton Bradley Park following the cessation of grazing when trees were planted. They showed that biological and biochemical processes associated with enhanced mineralization of organic P were significantly greater in soils where were clipping left compared to no mowing, which reflected increased organic matter inputs under the clippings return regime. In addition, studies of long-term changes in soil P under grazed pasture in New Zealand and elsewhere have clearly and consistently demonstrated that concentrations of soil organic P increased
Let us now test the predictions of our model in the context of the worldwide pharmaceutical industry. To this end, we shall first note that the pharmaceuti- cal industry is characterized by a positive net inflow of both new units (ψ > 0) and firms (b > 0). Secondly, a unit is naturally defined here as a molecular entity. New molecular entities are products developed by innovator companies, which after undergoing clinical trials translate into drugs that cure specific diseases. The num- ber of new molecular entities approved by the US Food and Drug Administration and similar agencies in other countries is widely used as a measure of innovation in pharmaceuticals (Pammolli et al. 2011). Since molecular units have different therapeutic properties, they cannot be substituted, and thus they can be credibly analyzed as independent submarkets (Sutton 1998). The whole pharmaceutical industry can be viewed as an aggregation of many independent units. Moreover, the sales of each unit are extremely volatile over the product lifecycle (V η > 0),
Th e particular case studies in this book sought to lay the groundwork needed for new ways of identifying and valuing innovation and creativity in Africa. Th e case study method helps to humanise otherwise abstract information and yields understanding into complex systems of interacting variables. Case stud- ies were thus chosen by the Open A.I.R. network as the necessary empirical tool for counteracting the formalistic tendencies of predominant IP measurements and analyses. Th e case study researchers adopted a range of methods. However, notwithstanding the Open A.I.R. network’s interdisciplinary framework, IP is a decidedly legal construct, making legally focused desk research, including statu- tory analysis, an important part of most of the studies. Most of the researchers analysed a range of materials on the legal and policy contexts for their studies, including international treaties, national policies, statutes and regulations, and scholarly articles. Th e researchers also consulted a range of non-legal, non-policy sources, in order to generate coherent socio-cultural and economic contexts for their studies. While two of the chapters contain statistical analyses and quantita- tive data collected through surveys (Chapter 15 on Botswana’s publicly funded researchers, and Chapter 8 on production and consumption of Egyptian inde- pendent music), most drew primarily on qualitative data from interviews, focus group discussions and qualitative written questionnaires. Such methods are not oft en used in legally oriented research (especially not regarding IP law), but are common in other areas of the social sciences. As will become clear to the reader, the qualitative data gathered were rich and facilitated author insights into a range of conceptual and practical elements, problems and solutions – insights which almost certainly could not have been generated via desk research alone.
sible for the initial accumulation of available nitrates in the soil. Biogeochemical rates are highly seasonal, as observed in experimental data. The development and appli- cation of SHIMMER not only provides important new insights into forefield dynamics, but also highlights aspects of these systems that require further field and laboratory research. The most pressing advances need to come in quantifying nutrient budgets
Lateral water flow and associated water redistribution across the landscape considerably influence hydrologic response in terrestrial ecosystems, including movement and storage of water in the soil (Guntner and Bronstert, 2004; Thomp- son and Moore, 1996). Some studies (e.g., Kim and Eltahir, 2004) indicated that topography drives lateral transport of water downslope, and water converges into concave areas or valleys through surface or subsurface runoff. As a result, wa- ter table depth tends to be significantly shallower in valleys compared to hills. However, this contrasting pattern did not occur in simulations that ignored water routing, in which the simulated water table depth and saturation deficit approxi- mated each other between valleys and hills/ridges of the wa- tershed (Fig. 3b and e). In other words, simulated water ta- ble depth and saturation deficit with water routing captured better our preconception of their spatial patterns across the watershed. A similar study in a humid watershed (Hotta et al., 2010) indicated that lateral flow and local infiltration de- scending from hillslopes often causes lower elevation sites to have a higher water table level and higher elevation sites to have a lower water table level.
The development of soil models has been common in the past and important in informing soil management, policy and prediction (McGill, 2007, 1996), for example in understand- ing the contribution of soil organic matter (SOM) to the for- mation of stable aggregate soils, the ease of soil cultivation, water holding characteristics and the risk of physical dam- age and compaction. The explicit inclusion of soil microbial dynamics has been shown to drastically improve the per- formance of these models (Wieder et al., 2013). There are many different types of soil models in use today across a range of scales and purposes, such as informing agricultural policy, understanding biogeochemical cycling and soil food webs and the feedbacks between soil processes, hydrology and the atmosphere (Stapleton et al., 2005; Blagodatsky and Richter, 1998; Knapp et al., 1983; Grant et al., 1993; German et al., 2012; Ingwersen et al., 2008; Leffelaar and Wessel, 1988; Kuijper et al., 2005; Kravchenko et al., 2004; Parton et al., 1988; Garnier et al., 2001; Darrah, 1991; Foereid and Yearsley, 2004; Vandewerf and Verstraete, 1987b; Long and Or, 2005; Maggi and Porporato, 2007; Moorhead and Sins- abaugh, 2006; Panikov and Sizova, 1996; Toal et al., 2000; Zelenev et al., 2000; Scott et al., 1995). However, although these models include an explicit microbial component, SOM models are tailored towards research questions that are fo- cussed on geochemistry and specifically organic matter dy- namics rather than biology. Forefield ecosystems are charac- terised by extreme and highly variable environmental condi- tions and rapidly changing compositions of microbial com- munities whose interplay results in unique chronosequence dynamics (Bradley et al., 2014). There is not a single model that can represent the unique forefield development without an unacceptable level of abstraction and simplification of the system.
Climate reconstructions from marine pollen records sug- gest that the Mediterranean environments may react with a reduced time lag to rapid climate changes (Fletcher et al., 2010). The response of the western Mediterranean ecosys- tems has even been synchronous with the North Atlantic variability during the last glacial period and the Holocene (Combourieu-Nebout et al., 2009). Changes in the pollen as- semblages of a marine record from the Alboran Sea also show very synchronous fluctuations between the surround- ing land ecosystem changes and the sea surface temperature fluctuations (Fletcher and Sánchez Goñi, 2008; Combourieu- Nebout et al., 2009). Pollen records from the Middle Atlas (Reille, 1976; Lamb and Van der kaars, 1995; Cheddadi et al., 2009; Rhoujjati et al., 2010; Nour el Bait et al., 2014; Tabel et al., 2016) and the Rif Mountains (Cheddadi et al., 2016) show that the Holocene climate change had a major impact on the ecosystems composition with a clear succession of different species sensitive to winter frost, strong rainfall sea- sonality, and/or the total amount of annual rainfall through- out the year.
between the environment and the species remain less well known. The long-term population dy- namics of aquatic insects could be meaningfully described with ANNs in addition to classical statistics. Regression and correlation models have repeatedly been used to explain patterns in com- munities and they provided useful insights on environmental control of ecosystems, but their predictive power is low (ter Braak and Verdon- schot, 1995; Paruelo and Tomasel, 1997; Walley and Fontama, 1998). With classical statistical methods and ordination (CCA; ter Braak, 1988, 1990), the variability between year abundance of individual species was attributed mainly to the discharge pattern during larval development (Wagner and Schmidt, 1999). Due to the necessity to recognise patterns and not single discharge events, ANNs are an alternative method to model species abundance (Colasanti, 1991; Lek et al., 1996).
But this situation has not arisen in a vacuum: UT is relatively young and innovative university in an old industrial region Founded in 1961, UT’s main regional mission was to support the survival of the textiles industry and its diversification by increasing the number of highly trained engineers (Schutte, 1999). However, from the 1970s, UT suffered as the textiles industry declined, leading to calls to close the university, and UT reinvented itself as a source of new industries, developing strong leadership and support structures to promote entrepreneurship (Clark, 1998). Today, the university has 10,000 students and 3,300 staff in social and technical sciences, with a research focus in five areas (each with a corresponding research centre, listed in brackets): nanotechnology (MESA+), telematics and information technology (CTIT), biomedical technology and technical medicine (MIRA), innovation and governance studies (IGS) and Geo- information science and earth observation (ITC).