Probability modelling to reduce decision uncertainty in environmental niche identification and driving factor analysis: CaNaSTA case studies

Hillside agro-ecosystems have a complex spatial and temporal distribution of natural resources. Farmers generally possess a vast body of knowledge about environmental resources on their farms but this knowledge is largely based on locally observable features rather than generalized knowledge. The lack of process-based knowledge concerning agro-ecosystem function creates uncertainty that obstructs sound decision-making under conditions of rising economic and ecologic pressure in many developing countries. Since the past decade, Precision Agriculture provides tools to reduce uncertainty caused by environmental variation. By describing spatial and temporal variation of the environment, Geographic Information Systems help to detect suitable crops for specific environmental niches and support farmers to find optimal management practices for their plot of land. Hence Precision Agriculture helps to raise the economic benefits of farming, ensures consistent product quality and reduces negative environmental impacts caused by inappropriate management practices. A spatial decision support system called CaNaSTA was developed to aid the decision making process of crop adoption in tropical agriculture. Using Bayesian probability statistics, CaNaSTA integrates trial data, spatial data and expert knowledge and provides maps, tables and graphs analyzing and interpreting the probability distributions of spatial phenomena. The International Centre for Tropical Agriculture (CIAT) has applied CaNaSTA to three case studies related to tropical agriculture. The first case study identifies niches for specialty coffee production, the second analyses the potential of cowpea (Vigna unguiculata (L.) Walp.) for tropical hillside environments in Colombia. Finally, Canasta was applied to a non-crop related area by performing a study of carbon concentration in tropical soils.

Deep Learning for Fatigue Estimation on the Basis of Multimodal Human-Machine Interactions

The new method is proposed to monitor the level of current physical load and accumulated fatigue by several objective and subjective characteristics. It was applied to the dataset targeted to estimate the physical load and fatigue by several statistical and machine learning methods. The data from peripheral sensors (accelerometer, GPS, gyroscope, magnetometer) and brain-computing interface (electroencephalography) were collected, integrated, and analyzed by several statistical and machine learning methods (moment analysis, cluster analysis, principal component analysis, etc.). The hypothesis 1 was presented and proved that physical activity can be classified not only by objective parameters, but by subjective parameters also. The hypothesis 2 (experienced physical load and subsequent restoration as fatigue level can be estimated quantitatively and distinctive patterns can be recognized) was presented and some ways to prove it were demonstrated. Several "physical load" and "fatigue" metrics were proposed. The results presented allow to extend application of the machine learning methods for characterization of complex human activity patterns (for example, to estimate their actual physical load and fatigue, and give cautions and advice).Comment: 12 pages, 10 figures, 1 table; presented at XXIX IUPAP Conference in Computational Physics (CCP2017) July 9-13, 2017, Paris, University Pierre et Marie Curie - Sorbonne (https://ccp2017.sciencesconf.org/program

Distribución y abundancia de Parastichopus parvimensis (Holothuroidea) en islas de la costa occidental de Baja California Sur, México, durante el periodo reproductivo

The distribution and abundance of the warty sea cucumber Parastichopus parvimensis in the islands Natividad (NI), Asunción (AI) and San Roque (SRI) on the western coast of Baja California Sur (BCS), Mexico, were examined based in independent data from commercial fishing in March and April 2009. The density was estimated from 345 sample units (SU = 10 m2 ) random selected between 2 and 30 m of depth. In NI, AI and SRI was found an average density and standard deviation (S) of 1.1 (1.02), 0.82 (1.06) and 0.83 (0.9) org/m2, and an average gutted weight of 158, 176, and 149g respectively. Changes in density were analyzed using a generalized linear model (GLM) with Gamma error structure, using the variables of depth and zone (islands) as well as the interaction effect, which was significant (p < 0.01). The analysis revealed a pattern of increasing density with the depth in SRI (p < 0.01) and non-significant in NI and AI. The variability of the density was high at all depths in NI (S = 10.2) and AI (S = 10.6), while SRI was only in >10 m depth (S = 9.0), but much less in water shallow (S = 2.7). The way in which the density varies on each island seems to be modulated by physical and biological characteristics related to the substrate, since 85% of the sampling units were associated with rocky substrate. We discuss possible factors that could influence the density changes with depth.Se estudió la distribución y abundancia del pepino de mar Parastichopus parvimensis, utilizando datos independientes de la pesca comercial en las islas Natividad (IN), Asunción (IA) y San Roque (ISR) de la costa occidental de Baja California Sur (BCS), México, en marzo y abril de 2009. La densidad se estimó a partir de 345 unidades de muestra de 10 m2 (UM) distribuidas al azar entre 2 y 30 m de profundidad. En IN, IA e ISR se encontró una densidad promedio y desviación estándar (S) de 1.1 (1.02), 0.82 (1.06) y 0.83 (0.9) org/m2 , y un peso eviscerado promedio de 158, 176, y 149 g respectivamente. Los cambios en densidad se analizaron con un Modelo Lineal Generalizado (MLG) con estructura de error Gamma, en función de las variables de profundidad y zona, así como del efecto de interacción entre ambas, el cual resultó significativo (p < 0.01). El análisis reveló un patrón de densidad creciente con la profundidad en ISR (p < 0.01) y no significativo en IN e IA. La variabilidad de la densidad fue alta en todas las profundidades en IN (S = 10.2) e IA (S = 10.6), mientras que en ISR solamente fue en más de 10 m de profundidad (S = 9.0), y mucho menor en aguas someras (S = 2.7). La forma en que varió la densidad en cada isla, parece estar modulada por características físicas y biológicas relacionadas al sustrato, ya que el 85% de las unidades de muestreo estuvieron asociadas a sustrato rocoso. Se discuten posibles factores que pueden influir en los cambios de la densidad con la profundidad

Caracterización experimental del comportamiento elasto-plástico con daño continuo de un suelo granular mejorado con fibras de polipropileno

El presente trabajo se limita a caracterizar de manera experimental el comportamiento elastoplástico con daño continuo en un suelo granular previamente reforzado con diferentes porcentajes de fibras de polipropileno, sometiéndolo a ciclos de carga y descarga.CONACYT – Consejo Nacional de Ciencia y Tecnologí

Network analysis of sea turtle movements and connectivity: A tool for conservation prioritization

Aim: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location: Global. Methods: We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.Fil: Kot, Connie Y.. University of Duke; Estados UnidosFil: Åkesson, Susanne. Lund University; SueciaFil: Alfaro Shigueto, Joanna. Universidad Cientifica del Sur; Perú. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Amorocho Llanos, Diego Fernando. Research Center for Environmental Management and Development; ColombiaFil: Antonopoulou, Marina. Emirates Wildlife Society-world Wide Fund For Nature; Emiratos Arabes UnidosFil: Balazs, George H.. Noaa Fisheries Service; Estados UnidosFil: Baverstock, Warren R.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Blumenthal, Janice M.. Cayman Islands Government; Islas CaimánFil: Broderick, Annette C.. University of Exeter; Reino UnidoFil: Bruno, Ignacio. Instituto Nacional de Investigaciones y Desarrollo Pesquero; ArgentinaFil: Canbolat, Ali Fuat. Hacettepe Üniversitesi; Turquía. Ecological Research Society; TurquíaFil: Casale, Paolo. Università degli Studi di Pisa; ItaliaFil: Cejudo, Daniel. Universidad de Las Palmas de Gran Canaria; EspañaFil: Coyne, Michael S.. Seaturtle.org; Estados UnidosFil: Curtice, Corrie. University of Duke; Estados UnidosFil: DeLand, Sarah. University of Duke; Estados UnidosFil: DiMatteo, Andrew. CheloniData; Estados UnidosFil: Dodge, Kara. New England Aquarium; Estados UnidosFil: Dunn, Daniel C.. University of Queensland; Australia. The University of Queensland; Australia. University of Duke; Estados UnidosFil: Esteban, Nicole. Swansea University; Reino UnidoFil: Formia, Angela. Wildlife Conservation Society; Estados UnidosFil: Fuentes, Mariana M. P. B.. Florida State University; Estados UnidosFil: Fujioka, Ei. University of Duke; Estados UnidosFil: Garnier, Julie. The Zoological Society of London; Reino UnidoFil: Godfrey, Matthew H.. North Carolina Wildlife Resources Commission; Estados UnidosFil: Godley, Brendan J.. University of Exeter; Reino UnidoFil: González Carman, Victoria. Instituto National de Investigación y Desarrollo Pesquero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Harrison, Autumn Lynn. Smithsonian Institution; Estados UnidosFil: Hart, Catherine E.. Grupo Tortuguero de las Californias A.C; México. Investigacion, Capacitacion y Soluciones Ambientales y Sociales A.C; MéxicoFil: Hawkes, Lucy A.. University of Exeter; Reino UnidoFil: Hays, Graeme C.. Deakin University; AustraliaFil: Hill, Nicholas. The Zoological Society of London; Reino UnidoFil: Hochscheid, Sandra. Stazione Zoologica Anton Dohrn; ItaliaFil: Kaska, Yakup. Dekamer—Sea Turtle Rescue Center; Turquía. Pamukkale Üniversitesi; TurquíaFil: Levy, Yaniv. University Of Haifa; Israel. Israel Nature And Parks Authority; IsraelFil: Ley Quiñónez, César P.. Instituto Politécnico Nacional; MéxicoFil: Lockhart, Gwen G.. Virginia Aquarium Marine Science Foundation; Estados Unidos. Naval Facilities Engineering Command; Estados UnidosFil: López-Mendilaharsu, Milagros. Projeto TAMAR; BrasilFil: Luschi, Paolo. Università degli Studi di Pisa; ItaliaFil: Mangel, Jeffrey C.. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Margaritoulis, Dimitris. Archelon; GreciaFil: Maxwell, Sara M.. University of Washington; Estados UnidosFil: McClellan, Catherine M.. University of Duke; Estados UnidosFil: Metcalfe, Kristian. University of Exeter; Reino UnidoFil: Mingozzi, Antonio. Università Della Calabria; ItaliaFil: Moncada, Felix G.. Centro de Investigaciones Pesqueras; CubaFil: Nichols, Wallace J.. California Academy Of Sciences; Estados Unidos. Center For The Blue Economy And International Environmental Policy Program; Estados UnidosFil: Parker, Denise M.. Noaa Fisheries Service; Estados UnidosFil: Patel, Samir H.. Coonamessett Farm Foundation; Estados Unidos. Drexel University; Estados UnidosFil: Pilcher, Nicolas J.. Marine Research Foundation; MalasiaFil: Poulin, Sarah. University of Duke; Estados UnidosFil: Read, Andrew J.. Duke University Marine Laboratory; Estados UnidosFil: Rees, ALan F.. University of Exeter; Reino Unido. Archelon; GreciaFil: Robinson, David P.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Robinson, Nathan J.. Fundación Oceanogràfic; EspañaFil: Sandoval-Lugo, Alejandra G.. Instituto Politécnico Nacional; MéxicoFil: Schofield, Gail. Queen Mary University of London; Reino UnidoFil: Seminoff, Jeffrey A.. Noaa National Marine Fisheries Service Southwest Regional Office; Estados UnidosFil: Seney, Erin E.. University Of Central Florida; Estados UnidosFil: Snape, Robin T. E.. University of Exeter; Reino UnidoFil: Sözbilen, Dogan. Dekamer—sea Turtle Rescue Center; Turquía. Pamukkale University; TurquíaFil: Tomás, Jesús. Institut Cavanilles de Biodiversitat I Biologia Evolutiva; EspañaFil: Varo Cruz, Nuria. Universidad de Las Palmas de Gran Canaria; España. Ads Biodiversidad; España. Instituto Canario de Ciencias Marinas; EspañaFil: Wallace, Bryan P.. University of Duke; Estados Unidos. Ecolibrium, Inc.; Estados UnidosFil: Wildermann, Natalie E.. Texas A&M University; Estados UnidosFil: Witt, Matthew J.. University of Exeter; Reino UnidoFil: Zavala Norzagaray, Alan A.. Instituto politecnico nacional; MéxicoFil: Halpin, Patrick N.. University of Duke; Estados Unido

Consideraciones para la consolidación estructural del templo Concepción la conquistadora de Salcajá

El Templo Concepción la Conquistadora de Salcajá es el resultado de la evolución de la primera ermita construida en el Reino de Guatemala (Centro América) en la época colonial; la construcción data de 1524, contiene en su interior los retablos posiblemente más antiguos de Centroamérica y la primera virgen traída del viejo continente; es una joya arquitectónica invaluable en Guatemala y de allí deriva la importancia de su conservación. En el año 2002 se realizó un análisis del estado del templo y se presentó una propuesta para su consolidación estructural. Para hacer la propuesta fue necesario reflexionar sobre la importancia de entender el funcionamiento estructural de la construcción original y el mecanismo de transmisión de fuerzas concebido por sus diseñadores y constructores. Además, se analizaron los factores que pudieron haber modificado el diseño original y afectado la seguridad estructural, en función de los sismos, hundimientos del suelo, deterioro por intemperismo, agentes químicos, acción de la humedad y erosión por lluvias, así como por las modificaciones hechas a lo largo de los años. Para la propuesta de consolidación se trabajó en tres etapas: a) descripción del templo; b) diagnóstico del estado de las estructuras en 2002 e identificación de sus debilidades y c) propuesta para su consolidación estructural. El templo fue intervenido durante los años 2002 y 2003, aplicando la propuesta planteada. Se consideró oportuno hacer una evaluación del estado de las estructuras en el año 2015, después de 12 años de la intervención, tiempo durante el cual la edificación ha estado en servicio sin daños por los fuertes sismos que han ocurrido en los alrededores, originados por los desplazamientos de la Placa Tectónica de Norteamérica y la del Caribe, así como por la concurrencia de la Placa de Cocos. El templo se encuentra en buen estado, considerándose exitosa la propuesta implementada en el año 2002. En este trabajo se incluye un resumen de la propuesta para la consolidación y la evaluación de su estado en el año 2015

Growth and length-weight relationship of the striped marlin, Tetrapturus audax (Pisces: Istiophoridae), in Cabo San Lucas, Baja California Sur, Mexico

 To determine the age, backcalculate the length, and describe the individual growth and length-weight relationship of the striped marlin Tetrapturus audax, the catch of the sport-fishing fleet from Cabo San Lucas, Mexico, was sampled from 1988 to 1993. The length and weight of 1044 fishes were measured, and the fourth spine of the dorsal fin was collected from 399 of them. The mandibular length (ML) ranged from 156 to 263 cm, and the total weight (TW) ranged from 26 to 100 kg. No significant differences were detected (P > 0.05) in the ML-TW relationship either between sexes or between years. The general relationship was TW = 0.00008*ML(2.523), showing a negative allometric growth (b < 3, P < 0.05). Ten age groups were determined (2 to 11). The relationship between ML and the dorsal fin radius was highly significant (P < 0.001), justifying the use of the dorsal fin for the age determination and to describe the growth of the striped marlin. The von Bertalanffy growth model was fitted appropriately to backcalculated ML-age data (r2 = 0.99) and the values of the parameters were: L∞ = 221 cm, K = 0.23 per year, and t0 = –1.6. The striped marlin reaches 45% of the asymptotic length in its first year of life; in the second year the growth rate decreases to 10%, and during the next eight years the growth rate is 4% on average. The present study is the first to report on the individual growth of the striped marlin based on age determination in hard structures

ESTUDIO DE LAS CORRIENTES IONICAS EN CELULAS CARDIACAS AISLADAS DEL SAPO Bufo marinus

International audienceA simple enzymatic dissociation method is described to obtain isolated cells from the atrium of adult toad Bufo marinus. The electrical activity of single cells were recorded with the whole -cell patch clamp technique. Action potential characteristics and Na, K, and Ca currents are compared to those measured on uni- or multicellular cardiac preparations from other adult amphibians.Se describe un merodo simple de diaociacion enzirnatica para obrener celulas aisladas de la audcula del sapo Bufo marinus. La actividad electrics de las celulas aisladas se registro con la tecnica del patch clamp de celula entera. Las caracterfsticas de) potencial de accion y de las corrientes de Na, K y Ca se comparan con aquellas medidas en preparaciones de otros anfibios adulto