Aim/Purpose: The objective of this paper is to review the vast literature of user-centric in-formation science and inform about the emerging themes in information behaviour science. Background: The paradigmatic shift from system-centric to user-centric approach facilitates research on the cognitive and individual information processing. Various information behaviour theories/models emerged. Methodology: Recent information behaviour theories and models are presented. Features, strengths and weaknesses of the models are discussed through the analysis of the information behaviour literature. Contribution: This paper sheds light onto the weaknesses in earlier information behaviour models and stresses (and advocates) the need for research on social information behaviour. Findings: Prominent information behaviour models deal with individual information behaviour. People live in a social world and sort out most of their daily or work problems in groups. However, only seven papers discuss social information behaviour (Scopus search). Recommendations for Practitioners : ICT tools used for inter-organisational sharing should be redesigned for effective information-sharing during disaster/emergency times. Recommendation for Researchers: There are scarce sources on social side of the information behaviour, however, most of the work tasks are carried out in groups/teams. Impact on Society: In dynamic work contexts like disaster management and health care settings, collaborative information-sharing may result in decreasing the losses. Future Research: A fieldwork will be conducted in disaster management context investigating the inter-organisational information-sharing.

Aim/Purpose: Many disciplines have addressed the issue of “fake news.” This topic is of central concern to the transdiscipline of Informing Science, which endeavors to understand all issues related to informing. This paper endeavors to build a model to address not only fake news but all informing and misin-forming. To do this, it explores how errors get into informing systems, the issue of bias, and the models previously created to explore the complexity of informing. That is, this paper examines models and frameworks proposed to explore informing in the presence of bias, misinformation, disinformation, and fake news from the perspective of Informing Science. It concludes by intro-ducing a more nuanced model that considers some of the topics explored in the paper Methodology: The issue of informing and disinforming crosses many disciplinary perspectives. Each discipline puts on blinders that limit what it can contribute to its understanding of research topics. It is like trying to study a forest by seeing only the trees and not the animals or the animals but not the trees. Research perspectives that cross disciplinary boundaries are needed to more fully understand complex phenomena. This paper lays out some fundamental cross-disciplinary issues including how errors find their way into informing systems, the issue of bias, and the frameworks used to model this phenomenon. Contribution: The paper introduces the competition framework for understanding informing and misinforming. This framework addresses many of the limitation of prior frameworks. Future Research: The concluding framework offers insights into understanding informing and disinforming. But this framework offers no insights into other forms of informing that are less well explored, such as song, dance, physical art, and architecture. Likewise, this framework does nothing to help the un-derstanding of informing via fideism or psychedelic revelation.

The purpose of this paper is to provide a model to help explain why ideas about reality differ. Misinformation is an important topic that in the past several years has gained prominence. The author developed a model of informing.

Aim/Purpose: This study offers an important contribution to the literature on couple social comparisons by showing how different aspects of comparisons are related to relationship quality. Background: Making social comparisons is a daily tendency of human beings that does not only occur on an individual level but also in the context of romantic relationships. This phenomenon is widespread among couples, though partners differ in terms of their propensity to make couple social comparisons. The literature has shown that all these facets of couple social comparison play an important role in relationship functioning. Methodology: In the current study of 104 young adults in a heterosexual relationship, we investigated the association of couple social comparison propensity, explicit couple social comparisons, and implicit couple social comparisons with couple relationship quality in terms of commitment and relationship satisfaction. Contribution: So far, studies have not tested all these aspects in predicting partners’ relationship quality. Findings: Results showed that commitment was negatively predicted by relationship social comparison propensity and positively predicted by implicit couple social comparisons, while relationship satisfaction was positively predicted by both implicit and explicit couple social comparisons. Recommendation for Researchers: Our results have implications for couple interventions. In preventive interventions, sustaining a positive view of one’s relationship may promote relationship satisfaction and commitment. Future Research: Future research should adopt a dyadic design to investigate cross-partner associations.

An optimisation-based decision-making support is proposed in this study in the form of fuzzy-probabilistic programming, which can be used to solve integrated order allocation, production planning, and inventory management problems in fuzzy and probabilistic uncertain environments. The problem was modelled in an uncertain mathematical optimisation model with two objectives: maximising the expectation of production volume and minimising the expectation of total operational cost subject to demand and other constraints. The model belongs to fuzzy-probabilistic bi-objective integer linear programming, and the generalised reduced gradient method combined with the branch-and-bound algorithm was utilised to solve the derived model. Numerical simulations were performed to illustrate how the optimal decision was formulated. The results showed that the proposed decision-making support was successful in providing the optimal decision with the maximum expectation of the production volume and minimum expectation of the total operational cost. Therefore, the approach can be implemented by decision-makers in manufacturing companies.

Data envelopment analysis (DEA) is widely used in various fields and for various models. Inverted data envelopment analysis (inverted DEA) is an extended model of DEA. Regression analysis (RA) is a statistical process for estimating the relationships among variables based on the model of averaged image. There are no essential relations among DEA and RA and inverted DEA. We creatively combine DEA, RA and inverted DEA to propose a new model: DEA-RA-Inverted DEA model. The model realises the efficiency estimation and evaluation through a discussion of the residual variables and the residual ratio coefficients. In addition, we will demonstrate the effectiveness of the model by applying it to efficiency estimation and evaluation of 16 Chinese logistics enterprises.

This study addresses a critical chain project scheduling (CCPS) problem regarding the feeding buffer. The main contribution of this study lies in determining the critical chain when the feeding buffer is considered along with the project buffer, a less addressed issue in the critical chain literature. Using a mixed-integer nonlinear programming (MINLP) model, the critical chain of a project with no break-down and no overflow is found. Moreover, the impact of the feeding buffer on the criticality of activities is discussed. The problem is solved using the Lingo software package for validation in small-sized instances. Since the CCPS is known as an NP-hard problem, a genetic algorithm (GA) is also designed to solve large-scale instances. The algorithm's performance is confirmed using various project scheduling library test problems. Sensitivity analysis is implemented based on some crucial parameters, and the critical chain is analysed after conducting several experiments. It is shown how considering the feeding buffer makes different critical chains and how shortlisting activities and resources are optimally managed.

Congcong FANG,Yun JIN,Guanlin CHEN,Yunfan ZHANG,Shidang LI,Yong MA,Yue XIE, Vol.E107-D, No.11, pp.1463-1467
Currently, an increasing number of tasks in speech emotion recognition rely on the analysis of both speech and text features. However, there remains a paucity of research exploring the potential of leveraging large language models like GPT-3 to enhance emotion recognition. In this investigation, we harness the power of the GPT-3 model to extract semantic information from transcribed texts, generating text modal features with a dimensionality of 1536. Subsequently, we perform feature fusion, combining the 1536-dimensional text features with 1188-dimensional acoustic features to yield comprehensive multi-modal recognition outcomes. Our findings reveal that the proposed method achieves a weighted accuracy of 79.62% across the four emotion categories in IEMOCAP, underscoring the considerable enhancement in emotion recognition accuracy facilitated by integrating large language models.
Publication Date: 2024/11/01

Takahito YOSHIDA,Takaharu YAGUCHI,Takashi MATSUBARA, Vol.E107-D, No.11, pp.1458-1462
Accurately simulating physical systems is essential in various fields. In recent years, deep learning has been used to automatically build models of such systems by learning from data. One such method is the neural ordinary differential equation (neural ODE), which treats the output of a neural network as the time derivative of the system states. However, while this and related methods have shown promise, their training strategies still require further development. Inspired by error analysis techniques in numerical analysis while replacing numerical errors with modeling errors, we propose the error-analytic strategy to address this issue. Therefore, our strategy can capture long-term errors and thus improve the accuracy of long-term predictions.
Publication Date: 2024/11/01

Nat PAVASANT,Takashi MORITA,Masayuki NUMAO,Ken-ichi FUKUI, Vol.E107-D, No.11, pp.1453-1457
We proposed a procedure to pre-process data used in a vector autoregressive (VAR) modeling of a temporal point process by using kernel density estimation. Vector autoregressive modeling of point-process data, for example, is being used for causality inference. The VAR model discretizes the timeline into small windows, and creates a time series by the presence of events in each window, and then models the presence of an event at the next time step by its history. The problem is that to get a longer history with high temporal resolution required a large number of windows, and thus, model parameters. We proposed the local density estimation procedure, which, instead of using the binary presence as the input to the model, performed kernel density estimation of the event history, and discretized the estimation to be used as the input. This allowed us to reduce the number of model parameters, especially in sparse data. Our experiment on a sparse Poisson process showed that this procedure vastly increases model prediction performance.
Publication Date: 2024/11/01

One of the main tasks in tax administration is debt management. The main goal of this function is tax due collection. Statements are processed in order to select strategies to use in the debt management process to optimise the debt collection process. This work proposes to carry out a data mining process to predict debts of taxpayers with high probability of non-payment. The data mining process identifies high-risk debts using a survival analysis on a dataset from a tax administration. Three groups of tax debtors with similar payment behaviour were identified and a success rate of up to 90% was reached in estimating the payment time of taxpayers. The concordance index (C-index) was used to determine the performance of the constructed model. The highest prediction rate reached was 90.37% corresponding to the third group.

To capture the complexity and diversity of systems with both technical and social features, modelling methods are needed that similarly provide various tools and concepts. Study of developed methods shows that despite all of their advantages and strengths, there is a need for a method that with a holistic approach integrates perspectives, strengths and tools of the developed methods and models with different aspects of socio-technical systems. The main aim of the current study is to design a method for modelling complex socio-technical systems. To achieve this goal, it is necessary to design a method that is based on creativity and existing knowledge base. Therefore, design science research is used as a research strategy to design proposed method. For the first time, design science research in the field of operations research has been used to design a modelling method. This study also presents new tools and concepts for modelling socio-technical systems.

In Italy, the reimbursement provided to healthcare organisations for medical and surgical procedures is based on the diagnosis related group weight (DRGW), which is an increasing function of the complexity of the procedures. This makes the reimbursement an upper unlimited function. This model does not include the relation of the volume with the complexity. The paper proposes a mathematical model for the optimisation of the reimbursement by determining the optimal mix of volume/procedure, considering the relation volume/complexity and DRGW/complexity. The decreasing, linear, and increasing returns to scale have been defined, and the optimal solution found. The comparison of the model with the traditional approach shows that the proposed model helps the healthcare system to discern the quantity of the reimbursement to provide to health organisations, while the traditional approach, neglecting the relation between the volume and the complexity, can result in an overestimation of the reimbursement.

Recent innovations in additive manufacturing (AM) have proven its efficacy for not only the manufacturing industry but also the healthcare industry. Researchers from Cal Poly, San Luis Obispo, and California State University Long Beach are developing a model that will determine the optimal locations for additive manufacturing hubs that can effectively serve both the manufacturing and healthcare industries. This paper will focus on providing an overview of the healthcare industry's unique needs for an AM hub and summarise the specific inputs for the model. The methods used to gather information include extensive literature research on current practices of AM models in healthcare and an inclusive survey of healthcare practitioners. This includes findings on AM's use for surgical planning and training models, the workflow to generate them, sourcing methods, and the AM techniques and materials used. This paper seeks to utilise the information gathered through literature research and surveys to provide guidance for the initial development of an AM hub location model that locates optimal service locations.

Ph.D. Dissertation Defense Modeling and Extracting Information about Cybersecurity Events from Text Taneeya Satyapanich 9:30-11:30 Monday, 18 November, 2019, ITE346? People now rely on the Internet to carry out much of their daily activities such as banking, ordering food, and socializing with their family and friends. The technology facilitates our lives, but also comes with […]

The post Defense: Taneeya Satyapanich, Modeling and Extracting Information about Cybersecurity Events from Text appeared first on UMBC ebiquity.

Building on prior work showing that abusive supervision is a reaction to subordinates' poor performance, we develop a self-control framework to outline when and why supervisors abuse poor performing subordinates. In particular, we argue poor performing subordinates instill in supervisors a sense of hostility towards the subordinate, which in turn leads to engaging in abusive supervision. Within this self-control framework, poor performance is more likely to lead to abusive supervision when (a) the magnitude of the hostility experienced is higher (e.g., for those with a hostile attribution bias), or (b) the translation of hostility into abusive supervision is unconstrained (e.g., for those who are low in trait mindfulness). In two experimental studies with full-time supervisors where we manipulated the independent variable (Study 1) and the mediator (Study 2), and in a multi-wave and multi-source field study with data collected from supervisor-subordinate teams (50 supervisors and 206 subordinates) at two time points (Study 3), we found overall support for our predictions. Implications for how to reduce the occurrence of abusive supervision in the workplace are discussed.

British Vogue's editor says skinny models are back "in", partly fuelled by weight loss drug Ozempic.

As we harness AI’s potential, specialised models for sectors like climate change offer a promising path forward.

The EUBrazilOpenBio project  announces two new training tools as a part of its e-training Programme aiming at educating and enabling current and potential users of EUBrazilOpenBio to unlock new knowledge and shape effective policy on biodiversity challenges. The new tools cover the following use cases: Ecological Niche Modeling and Cross-mapping.

The EUBrazilOpenBio anytime, anywhere eTraining tools are designed for researchers in the spheres of Biodiversity, Life science, Climate Change, application Developers as well as regulatory authorities and policy decision-makers.

EUBrazilOpenBio is focused on tackling the complexity of biodiversity science such as the diversity of multidisciplinary datasets spanning from climatology to earth sciences by integrating advanced computing resources with data sources across Europe and Brazil.

For more informationand to try out the new tools click here.

The Biodiversity Data Journal goes beyond the basics of the Gold Open Access

There are two main modes of open access publishing – Green Open Access, where the author has the right to provide free access to the article outside the publisher's web site in a repository or on his/her own website, and Gold Open Access, where articles are available for free download directly from the publisher on the day of publication.

Opening of content and data, however does not necessarily mean "easy to discover and re-use". The Biodiversity Data Journal proposed the term "Advanced Open Access" to describe an integrated, narrative (text) and data publishing model where the main goal is to make content "re-usable" and "interoperable" for both humans and computers.

To publish effectively in open access, it is not sufficient simply to provide PDF or HTML files online. It is crucial to put these under a reuse-friendly license and to implement technologies that allow machine-readable content and data to be harvested and collated into a big data pool.

The Advanced Open Access means:

• Free to read
• Free to re-use, revise, remix, redistribute
• Easy to discover and harvest
• Content automatically summarised by aggregators
• Data and narrative integrated to the widest extent possible
• Human- and computer-readable formats
• Community-based, pre- and post-publication peer-review
• Community ownership of data
• Free to publish or at low cost affordable by all

BDJ shortens the distance between "narrative" (text) and "data" publishing. Many data types, such as species occurrences, checklists, measurements and others, are converted into text from spreadsheets for better readability by humans. Conversely, text from an article can be downloaded as structured data or harvested by computers for further analysis.

"Open access is definitely one of the greatest steps in scientific communication comparable to the invention of the printing technology or the peer-review system. Great but not sufficient!" said Prof. Lyubomir Penev, founder of Pensoft Publishers and the Biodiversity Data Journal. "We need to switch the focus already from making content 'available for free download' to being discoverable and extractable. Such re-usability multiplies society's investment in science".

Additional information:

The Biodiversity Data Journal is designed by Pensoft Publishers and was funded in part by the European Union's Seventh Framework Program (FP7) project ViBRANT.

Source: Smith V, Georgiev T, Stoev P, Biserkov J, Miller J, Livermore L, Baker E, Mietchen D, Couvreur T, Mueller G, Dikow T, Helgen K, Frank J, Agosti D, Roberts D, Penev L (2013) Beyond dead trees: integrating the scientific process in the Biodiversity Data Journal. Biodiversity Data Journal 1: e995. DOI: 10.3897/BDJ.1.e995

Fauna Europaea started in 2000 as an EC-FP5 four-year project, delivering its first release in 2004. After 14 years of steady progress and successful participations in several EC projects, as a part of the EC-FP7 European Biodiversity Observation Network project (EU BON), to increase the general awareness of the work done by the contributors and to extend the general dissemination of the Fauna Europaea results, the Biodiversity Data Journal has applied its novel e-Publishing tools to prepare data papers for all 56 major taxonomic groups.

Fauna Europaea provides a public web-service with an index of scientific names (including important synonyms) of all living European land and freshwater animals, their geographical distribution at country level, and some additional information. The Fauna Europaea project covers about 230,000 taxonomic names, including 130,000 species name. This represents a huge effort by more than 400 contributing specialists throughout Europe and is a unique (standard) reference suitable for many users in science, government, industry, nature conservation and education.

'Contributions on Fauna Europaea' is the second series launched by the Biodiversity Data Journal after the Checklist of British and Irish Hymenoptera and the first one that embraces thematic data-papers structured in a common pattern extracted from a large database. This novel publication model will assemble in a single-issue 56 data-papers on different taxonomic groups covered by the Fauna Europaea project in the period 2000-2014 and a range of accompanying papers highlighting various aspects of this project (gap-analysis, software design, taxonomic assessments, etc.).

This is the first collection of data-papers of this scale. It will formalise and effectively publish the results of nearly 500 contributors building the largest European animal (taxonomic) database. The new publication model provides a reliable mechanism for citation and bibliographic indexing of large and uniformly structured databases.

"The publication of Fauna Europaea data papers brings a number of benefits for science, for example it stimulates experts to hand-over descriptive details on their groups, triggers new ways of community networking and participation, motivates experts to update their data, supports a better documentation of their achievements, including issues like 'micro-publications', and increase an ownership feeling with the associated effort" said Dr Yde de Jong, coordinator of the Fauna Europaea and Pan-European Species directories Infrastructure (PESI) projects.

The launch of this large collection of data papers coincides with one more cutting-edge innovation of the Biodiversity Data Journal, the publication of an API, a first of its kind, to import complex and data-rich manuscripts, which include text, data, images, in-text citations, references, in fact anything that a manuscript may contain.

"I am happy that these exciting innovations coincided with the first birthday of the Biodiversity Data Journal. Just a year ago we launched this new concept with the motto: Making your data count! These novel approaches and tools are an excellent example how our concept evolved!" comments Prof. Lyubomir Penev, Managing Director of Pensoft Publishers.

Original Sources:

de Jong Y, Verbeek M, Michelsen V, Bjørn P, Los W, Steeman F, Bailly N, Basire C, Chylarecki P, Stloukal E, Hagedorn G, Wetzel F, Glöckler F, Kroupa A, Korb G, Hoffmann A, Häuser C, Kohlbecker A, Müller A, Güntsch A, Stoev P, Penev L (2014) Fauna Europaea – all European animal species on the web. Biodiversity Data Journal 2: e4034. doi: 10.3897/BDJ.2.e4034

Gibson D, Bray R, Hunt D, Georgiev B, Scholz T, Harris P, Bakke T, Pojmanska T, Niewiadomska K, Kostadinova A, Tkach V, Bain O, Durette-Desset M, Gibbons L, Moravec F, Petter A, Dimitrova Z, Buchmann K, Valtonen E, de Jong Y (2014) Fauna Europaea: Helminths (Animal Parasitic). Biodiversity Data Journal 2: e1060. doi: 10.3897/BDJ.2.e1060

The Mediterranean Institute for Biodiversity and Ecology (IMBE, Aix-Marseille University, Aix-en-Provence, France), in its research group "Macroecology and Biogeography of Global Change (MacroBio)" has a PostDoc position open for applications. The post has a duration of 36 months, the initial contract is made for 18 months, being extended based on an assessment of performance. The position is funded by the European Commission through the FP7 Research Project LUC4C and affiliated to the French National Scientific Research Centre (CNRS).

The main topic is to improve the way LULCC processes are represented in the DGVM LPJmL through enhanced soil and vegetation process representation. Work should improve the model's capacity to project climate-LULCC interactions for the computation of net climate effects, and ecosystem services. One focus is on the representation of diverse agricultural management systems, cropland abandonment/afforestation and forest management, in order to develop ways to account for their effects on biochemical cycles and biophysics.

A Special Section: "Conservation in Europe as a model for emerging conservation issues globally" is featured in the Early View module of Conservation Biology online. The section includes: 

Mapping opportunities and challenges for rewilding in Europe

Silvia Ceaușu, Max Hofmann, Laetitia M. Navarro, Steve Carver, Peter H. Verburg and Henrique M. Pereira

John D. C. Linnell, Petra Kaczensky, Ulrich Wotschikowsky, Nicolas Lescureux and Luigi Boitani

DOI: 10.1111/cobi.12534

Post-doctoral scientist position is open for the project "Towards an integrated prediction of Land & Sea Responses to global change in the Mediterranean Basin" (LaSeR-Med), which focusses on integrated socio-ecological modelling. The duration of the contract is initially one year, with a possible extension for a second year, depending on the initial results. The post-doc will be based within the Mediterranean Institute of marine and terrestrial Biodiversity and Ecology (IMBE) in Aix-en-Provence, France. The project is part of the Labex OT-Med (http://www.otmed.fr/).

Applicants should hold a doctoral degree in physics, chemistry, microbiology, geosciences, environmental sciences or a related field of science. They should be familiar with modelling biogeochemical interactions between ecosystems and capable to further develop existing numerical ecosystem models. Programming skills (C) and modelling experience are therefore mandatory. Knowledge of R and of Unix/Linux environment will be an advantage. The candidate should have good written and oral communication skills. For work, good skills in the English language will be essential.

The project:

Terrestrial and marine ecosystems are connected through groundwater, river discharge and nutrient outflows (especially N and P). River catchments in the Mediterranean are N-intensive regions, mostly due to intensive agriculture in the North and to crop N2 fixation or food & feed import in the South. The fraction of nutrient reaching the sea constitutes significant anthropogenic forcing of many marine biological processes. For simulating the dynamics of the first levels of the marine food web (from nutrients to jellyfishes), the ocean biogeochemical model, Eco3M-MED, used and developed by the Mediterranean Institute of Oceanography (MIO) within OT-Med, currently uses N and P measurements at river mouths, e.g. for the Rhône.

In order to estimate the impacts of global change on the functioning of marine ecosystems, the project aims at modeling the dependency of N and P outflows to the Mediterreanean sea toward land management. Land management is modelled as part of the agro-ecosystem model LPJmL (Bondeau et al., 2007), that has been especially adapted to the Mediterranean cropping systems (Fader et al., 2015). Among others, LPJmL simulates the daily carbon and water cycles, and the river discharges to the sea. Following existing approaches in the scientific literature, the post-doc will implement the nutrient N and P transfer in LPJmL, covering the net nutrient inputs to the river catchments by accounting for the processes occurring at the agro-ecosystem level (N2 biological fixation, fertilization, atmospheric deposition) and the net food and feed imports. Since only a minor fraction of the net nutrient inputs from Mediterranean basins reaches the sea, the retention along the nutrient cascade will have to be added to the LPJmL river routing scheme, similarly to the method used by the Riverstrahler model. Once the nutrient transfers have been introduced into LPJmL, simulations will be validated using current climate and land use forcing for comparisons with the existing observations from river outlets. Finally, future conditions will be assessed by using the model with scenarios of changing regional climate and land use / land management.

Your application:

Applications should contain a suitable motivation letter describing your anticipated role in the project, a CV, a list of scientific publications and the names of at least two scientists that can be contacted for references. They must be sent to Ms. Gabriela Boéri (gabriela.boeri@imbe.fr). Please prepare your application as a single file in pdf-format.

Questions about the project or the position can be directed to Dr. Alberte Bondeau (alberte.bondeau@imbe.fr). The position will be filled as soon as a suitable candidate has been found – work should start soon after that date. The salary and contract conditions will be determined according to standards set by Aix-Marseille University – questions in this regard can be directed to Sophie Pekar (pekar@otmed.fr).

A new EU BON acknowledging data article provides a virtual species set as a valuable tool in biodiversity monitoring. 

Abstract

Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation. In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a dataset containing more than 700,000 random observations at the extent of Europe. The dataset includes spatial attributes such as: distance to roads, protected areas, country codes, and the habitat suitability of two spatially clustered species (grassland and forest species) and a wide-spread species.

Original Source:

Garzon-Lopez, C.X., Bastin, L., Foody, G.M., Rocchini, D. (2016). A virtual species set for robust and reproducible Species Distribution Modelling tests. Data in Brief, 7: 476-479. doi: http://dx.doi.org/10.1016/j.dib.2016.02.058

A new editorial, published in the Journal of Apllied Ecology looks at modelling and monitoring as methods for adaptive biodiversity management in the 21st century.

Abstract: 

With increasing threats on biodiversity, informed conservation decisions need to be based on currently observed and future predicted trends of biodiversity (Pereira, Navarro & Martins 2012; Guisan et al. 2013). In this regard, two essential components supporting informed biodiversity conservation decisions are good monitoring data to assess recent and ongoing trends (Collen et al. 2013; Pereira et al. 2013) and robust models to anticipate possible future trends (Pereira et al. 2010a; Akc
akaya et al. 2016). Models benefit from robust monitoring data sets, that is repeated observations of biodiversity, as they need data to be fitted or validated, but models can also help assess data representativeness (e.g. by highlighting any bias), support proper data collection (e.g. covering the relevant gradients) or be used to make more effective use of biodiversity observations (Guisan et al. 2006, 2013; Ferrier 2011).

Read more in the open access paper.

The "International Workshop Decision Models and Population Management" will take place from 2 to 4 February, 2014 in Paris, France. The three days international and interdisciplinary workshop is devoted to the decision making, in particular in presence of multiple actors with or without interaction. These problems occur in a natural way in management of populations, where the dynamics are strongly related to the decisions. The workshop aims to bring together Mathematicians, Computer Scientists and Ecologists around the problem of populations management. The population dynamics, viability theory and game theory form an umbrella of helpful mathematical tools in this context. On the other hand, the computer sciences bring the online and algorithmic mechanism design.

The workshop is motivated by concrete problems proposed by ecologists and aims to create a synergy between scientists from different backgrounds to address the challenging modelling of decision making in the context of ecological paradigms.

Invited Speakers
- Michel BENAIM (Université de Neuchâtel, Neuchâtel, Swtizerland)
- Renato CASAGRANDI (Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano, Italy)
- Denis COUVET (Muséum National d'Histoire Naturelle, Paris, France)
- Sylvain DUCTOR (LIP6, UPMC, Paris, France)
- Marino GATTO (Dipartimento di Elettronica, Informazione e Bioingegneria-Politecnico di Milano, Italy) 
- Ihab HAIDAR (Sorbonne Universités, Paris, France)
- Sophie MARTIN (UR LISC - IRSTEA)
- Nicolas MAUDET (LIP6, UPMC, Paris, France) 
- Paco MELIÀ (Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano, Italy)
- Jean-Baptiste MIHOUB (UPMC-Sorbonne Universités, Paris, France)
- Vianney PERCHET (Université Denis Diderot, Paris, France)
 - Karl SIGMUND (University of Vienna, Wien, Austria)
- Sylvain SORIN (IMJ-PRG, UPMC, Paris, France)
- Jean-Philippe TERREAUX (IRSTEA-ADBX, Bordeaux, France)
- Tristan TOMALA (École des hautes études commerciales de Paris, Paris, France)
- Vladimir VELIOV (Institute of Statistics and Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria)
- Yannick VIOSSAT (Université Paris-Dauphine, Paris, France)

The conference covers scenarios and modelling applications in marine, freshwater and terrestrial systems, across all relevant disciplines of natural and social sciences. It is open to scientists and experts working in the field, policy makers and practioners. The conference focuses on: (i) Exploring recent advances in modelling human impacts on biodiversity and ecosystem services, (ii) Addressing the use of scenarios and models for decision support, (iii) Mobilising observations of biodiversity and ecosystem services for model development and testing, (iv) Capacity building for developing scenarios and models and for their use in decision making, (v) Horizon scanning and addressing gaps in knowledge.

More information available on the conference website.

The 10th  International Conference on Ecological Informatics 'Facing Global Change by Sharing Data and Models' wil take place on 24‐28 October 2016 in Dubrovnik, Croatia