This is an accepted manuscript of an article published by Taylor & Francis in International Journal of Computational Intelligence Systems, Vol. 7, No. 5, 993-1001 in October 2014, available online: http://dx.doi.org/10.1080/18756891.2014.967005 ; In this work, using the identification between implication operators and aggregation functions, we study the implication operators that are recovered from overlap functions. In particular, we focus in which properties of implication operators are preserved. We also study how negations can be defined in terms of overlap functions. ; This research has been partially supported by Grant TIN2013-40765-P from the Government of Spain and the Research Services of the Universidad Publica de Navarra.
We study the nature of regional inequality in Colombia over the past 200 years. The main empirical fact is that regional inequality has been highly persistent despite the large changes that have taken place and the modernization of the society. We show that regional inequality is highly correlated with significant within-country differences in economic and political institutions, which are themselves highly persistent over the same period. We propose a tentative political economy theory of why the spatial distribution of institutions and economic outcomes has been so persistent over time. ; Estudiamos la naturaleza de la desigualdad regional en Colombia durante los últimos 200 años. El principal hecho empírico es que la desigualdad regional ha sido muy persistente a pesar de los grandes cambios ocurridos y la modernización de la sociedad. Mostramos que la desigualdad regional está fuertemente correlacionada con diferencias significativas al interior del país en las instituciones económicas y políticas, que también son muy persistentes a lo largo del período. Proponemos una teoría tentativa de economía política para explicar por qué la distribución de las instituciones y los resultados económicos han sido tan persistentes en el tiempo.
The growth in data availability and in the number of users from non-spatial disciplines has increased the concern with spatial data management and spatial data quality. This reality contextualizes the need and importance of data quality management throughout the spatial data cycle related to data editing and sharing in the context of knowledge networks. The development of standard concepts, procedures and tools may foster important advances in the improvement of spatial dataset production, use and management practices. The implementation of environmental monitoring programs implies a growing number and diversity of users with specific capabilities and responsibilities. In this context, spatial data quality evaluation and management promotes communication, optimizes processes of analysis and spatial modelling, and in this sense improves research and political and technical decisionmaking and action. This paper focuses on the methods and tools currently available to evaluate the external quality of datasets for environmental and ecological monitoring. A novel framework is presented that allows integrating and interconnecting spatial data quality evaluation with metadata geoportals in WebGIS platforms, facilitating evaluation by users with often limited expertise in this field. The advances achieved in this research highlight the relevance of developing capacities for different users to improve data collection, data models, spatial data processing and modelling, but also the need to inform and report on spatial data quality using adequate tools.
The growth in data availability and in the number of users from non-spatial disciplines has increased the concern with spatial data management and spatial data quality. This reality contextualizes the need and importance of data quality management throughout the spatial data cycle related to data editing and sharing in the context of knowledge networks. The development of standard concepts, procedures and tools may foster important advances in the improvement of spatial dataset production, use and management practices. The implementation of environmental monitoring programs implies a growing number and diversity of users with specific capabilities and responsibilities. In this context, spatial data quality evaluation and management promotes communication, optimizes processes of analysis and spatial modelling, and in this sense improves research and political and technical decisionmaking and action. This paper focuses on the methods and tools currently available to evaluate the external quality of datasets for environmental and ecological monitoring. A novel framework is presented that allows integrating and interconnecting spatial data quality evaluation with metadata geoportals in WebGIS platforms, facilitating evaluation by users with often limited expertise in this field. The advances achieved in this research highlight the relevance of developing capacities for different users to improve data collection, data models, spatial data processing and modelling, but also the need to inform and report on spatial data quality using adequate tools.
Aim: Soil microbes are essential for maintenance of life‐supporting ecosystem services, but projections of how these microbes will be affected by global change scenarios are lacking. Therefore, our aim was to provide projections of future soil microbial distribution using several scenarios of global change. Location: Global. Time period: 1950–2090. Major taxa studied: Bacteria and fungi. Methods: We used a global database of soil microbial communities across six continents to estimate past and future trends of the soil microbiome. To do so, we used structural equation models to include the direct and indirect effects of changes in climate and land use in our predictions, using current climate (temperature and precipitation) and land‐use projections between 1950 and 2090. Results: Local bacterial richness will increase in all scenarios of change in climate and land use considered, although this increase will be followed by a generalized community homogenization process affecting > 85% of terrestrial ecosystems. Changes in the relative abundance of functional genes associated with the increases in bacterial richness are also expected. Based on an ecological cluster analysis, our results suggest that phylotypes such as Geodermatophilus spp. (typical desert bacteria), Mycobacterium sp. (which are known to include important human pathogens), Streptomyces mirabilis (major producers of antibiotic resistance genes) or potential fungal soil‐borne plant pathogens belonging to Ascomycota fungi (Venturia spp., Devriesia spp.) will become more abundant in their communities. Main conclusions: Our results provide evidence that climate change has a stronger influence on soil microbial communities than change in land use (often including deforestation and agricultural expansion), although most of the effects of climate are indirect, through other environmental variables (e.g., changes in soil pH). The same was found for microbial functions such as the prevalence of phosphate transport genes. We provide reliable predictions about the changes in the global distribution of microbial communities, showing an increase in alpha diversity and a homogenization of soil microbial communities in the Anthropocene. ; This manuscript was developed from discussions within the German Centre of Integrative Biodiversity Research funded by the Deutsche Forschungsgemeinschaft (DFG FZT118). C.A.G. and N.E. acknowledge funding by iDiv (DFG FZT118) Flexpool proposals 34600850 and 34600844. N.E. acknowledges funding by the DFG (FOR 1451) and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 677232). E.D. acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG GRK 2297 –314838170), MathCoRe. M.D.-B. acknowledges support from the Marie Sklodowska-Curie Actions of the Horizon 2020 Framework Program H2020-MSCA-IF-2016 under REA grant agreement number 702057. F.T.M. acknowledges support from the European Research Council grant agreement number 647038 (BIODESERT).
[Aim]: Invasive alien species (IAS) can cause profound impacts on ecosystem function and diversity, human health, well- being and livelihoods. Climate change is an important driver of biological invasions, so it is critical to develop models and climate- driven scenarios of IAS range shifts to establish preventive measures. In this study, we analyse how projected changes in the frequency and magnitude of climate extreme events could affect the spread of the six most widely distributed invasive vertebrate species in the Iberian Peninsula. ; [Location]: Iberian Peninsula. ; [Taxa]: Red avadavat (Amandava amandava), common waxbill (Estrilda astrild), monk parakeet (Myiopsitta monachus), rose- ringed parakeet (Psittacula krameri), American mink (Neovison vison) and pond slider (Trachemys scripta). ; [Methods]: We followed best- practice standards for species distribution models (SDMs) regarding handling of the response and predictor variables, model building and evaluation using metrics that assess different facets of model performance. We used an ensemble approach with four modelling methods of varying complexity, including both regression- based and tree- based machine- learning algorithms. We analysed five regional models for current (1971– 2000) and future climate (2021– 2050). We used principal components analysis to assess consensus among model outputs and positively weighed predictions from well- performing models. ; [Results]: Selected models showed high consensus and good predictive capacity on block cross- validation areas. Generalized Linear Models and Generalized Additive Models scored highest in reliability (calibration), but Bayesian Additive Regression Trees provided the best balance between calibration and discrimination capacity. Forecasts include visible changes in environmental favourability, with losses generally outweighing the gains, but with some areas becoming more favourable for several species. ; [Main conclusions]: Increased frequency and/or intensity of climate extreme events associated with ongoing climate change are projected to reduce overall invasion risk for the species examined although increases in favourability should be expected locally. ; This study was partially funded by the regional Government of Castilla- La Mancha through research projects POII10- 0076- 4195 and SBPLY/19/180501/000122. MBA's research on invasive species is supported by the Foundation for Science and Technology (FCT) within the framework of projects POCI- 01- 0145- FEDER- 030931 and PTDC/BIA- ECO/0207/2020. ; Peer reviewed
The research leading to these results has receivedfunding from the Spanish Ministry for Science andInnovation (MICINN; DPI2011-30090-C02-01),from the European Union's Horizon 2020 researchand innovation programme under the MarieSkłodowska–Curie grant agreement No. 712949(TECNIOspring PLUS) and from the Agency forBusiness Competitiveness of the Government ofCatalonia.e1026Acta Ophthalmologica2019 ; Preprint
Decreasing the use of pesticides is one of the main goals of current agriculture, which requires fast, precise and continuous assessments of crop pests. Citrus pests cause a lot of damage worldwide and the techniques to evaluate them are mainly based on manual, time-consuming readings of insects stuck on traps spread over the crops. This is the case of red scale insects, whose control is notably challenging due to their small size and high reproduction rate. Hence, in this work, we carry out a spectral characterization of this insect in the visible range through spectrometric devices, microscopy and hyperspectral imaging technology to analyze the feasibility of using this information as a means of automatically identifying specimens belonging to this species in this era of precision agriculture. The results obtained show that spectral reflectance differences between red scales and other insects can be recorded at long (red) wavelengths and that red scales are morphologically different, i.e., smaller and more rounded. A reflectance ratio computed from spectral images taken at 774 nm and 410 nm is proposed as a new approach for automated discrimination of red scales from other insects. ; This project has been co-financed by the European Union through the European Regional Development Fund (ERDF) and has the support of the Secretariat of Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya (Exp. 2019PROD00013) ; Peer Reviewed ; Postprint (published version)
Understanding the present and future distribution of soil-borne plant pathogens is critical to supporting food and fibre production in a warmer world. Using data from a global field survey and a nine-year field experiment, we show that warmer temperatures increase the relative abundance of soil-borne potential fungal plant pathogens. Moreover, we provide a global atlas of these organisms along with future distribution projections under different climate change and land-use scenarios. These projections show an overall increase in the relative abundance of potential plant pathogens worldwide. This work advances our understanding of the global distribution of potential fungal plant pathogens and their sensitivity to ongoing climate and land-use changes, which is fundamental to reduce their incidence and impacts on terrestrial ecosystems globally. ; This project received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 702057 and the European Research Council (ERC) grant agreements no. 242658 (BIOCOM) and no. 647038 (BIODESERT). M.D.-B. is supported by a Ramón y Cajal grant from the Spanish Government (agreement no. RYC2018-025483-I) and a MUSGONET grant (LRA17\1193) from the British Ecological Society. F.T.M. also acknowledges funding from Generalitat Valenciana (CIDEGENT/2018/041) and from sDiv, the synthesis centre of the German Centre for Integrative Biodiversity Research Halle–Jena–Leipzig (iDiv). Work on microbial distribution and colonization in the B.K.S. laboratory is funded by the Australian Research Council (DP190103714). B.K.S. also acknowledges a research award by the Humboldt Foundation. C.A.G. and N.E. acknowledge support from iDiv, funded by the German Research Foundation (DFG FZT118) through flexpool proposals 34600850 and 34600844. N.E. also acknowledges support from the ERC under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 677232).
14 páginas, 3 figuras, 2 tablas ; Research aimed at understanding the mechanisms underlying the relationship between tree diversity and antagonist infestation is often neglecting resource-use complementarity among plant species. We investigated the effects of tree species identity, species richness, and mycorrhizal type on leaf herbivory and pathogen infestation. We used a tree sapling experiment manipulating the two most common mycorrhizal types, arbuscular mycorrhiza and ectomycorrhiza, via respective tree species in monocultures and two-species mixtures. We visually assessed leaf herbivory and pathogen infestation rates, and measured concentrations of a suite of plant metabolites (amino acids, sugars, and phenolics), leaf elemental concentrations (carbon, nitrogen, and phosphorus), and tree biomass. Tree species and mycorrhizal richness had no significant effect on herbivory and pathogen infestation, whereas species identity and mycorrhizal type had. Damage rates were higher in arbuscular mycorrhizal (AM) than in ectomycorrhizal (EM) trees. Our structural equation model (SEM) indicated that elemental, but not metabolite concentrations, determined herbivory and pathogen infestation, suggesting that the investigated chemical defence strategies may not have been involved in the effects found in our study with tree saplings. Other chemical and physical defence strategies as well as species identity as its determinant may have played a more crucial role in the studied saplings. Furthermore, the SEM indicated a direct positive effect of AM trees on herbivory rates, suggesting that other dominant mechanisms, not considered here, were involved as well. We found differences in the attribution of elemental concentrations between the two rates. This points to the fact that herbivory and pathogen infestation are driven by distinct mechanisms. Our study highlights the importance of biotic contexts for understanding the mechanisms underlying the effects of biodiversity on tree-antagonist interactions. ; We thank Nicole M. van Dam, Henriette Uthe, Fredd Vergara, Martin Volf, and Alexander Weinhold for their valuable advice on metabolite analyses as well as Beate Rothe and Michael Reichelt for their help with chemical analyses. Moreover, comments by two anonymous reviewers helped to improve the paper. This work was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 677232). Further support came from the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and the EcoMetEoR platform, funded by the German Research Foundation (FZT 118). AMM acknowledges support from the program for attracting talent to Salamanca from Fundación Salamanca Ciudad de Cultura y Saberes and Ayuntamiento de Salamanca. ; Peer reviewed
Ecological monitoring programmes are designed to detect and measure changes in biodiversity and ecosystems. In the case of biological invasions, they can contribute to anticipating risks and adaptively managing invaders. However, monitoring is often expensive because large amounts of data might be needed to draw inferences. Thus, careful planning is required to ensure that monitoring goals are realistically achieved. Species distribution models (SDM s) can provide estimates of suitable areas to invasion. Predictions from these models can be applied as inputs in optimization strategies seeking to identify the optimal extent of the networks of areas required for monitoring risk of invasion under current and future environmental conditions. A hierarchical framework is proposed herein that combines SDM s, scenario analysis and cost analyses to improve invasion assessments at regional and local scales. We illustrate the framework with Acacia dealbata Link. (Silver‐wattle) in northern Portugal. The framework is general and applicable to any species. We defined two types of monitoring networks focusing either on the regional‐scale management of an invasion, or management focus within and around protected areas. For each one of these two schemes, we designed a hierarchical framework of spatial prioritization using different information layers (e.g. SDM s, habitat connectivity, protected areas). We compared the performance of each monitoring scheme against 100 randomly generated models. In our case study, we found that protected areas will be increasingly exposed to invasion by A. dealbata due to climate change. Moreover, connectivity between suitable areas for A. dealbata is predicted to increase. Monitoring networks that we identify were more effective in detecting new invasions and less costly to management than randomly generated models. The most cost‐efficient monitoring schemes require 18% less effort than the average networks across all of the 100 tested options. Synthesis and applications . The proposed framework achieves cost‐effective monitoring networks, enabling the interactive exploration of different solutions and the combination of quantitative information on network performance with orientations that are rarely incorporated in a decision support system. The framework brings invasion monitoring closer to European legislation and management needs while ensuring adaptability under rapid climate and environmental change.
