This document provides an introduction to species distribution modeling. It discusses why species distributions are modeled, the requirements for modeling including environmental variables and species occurrence records, appropriate software, and uses of distribution models. Validation of models is also addressed, such as evaluating whether the environmental variables used to generate a model are suitable. Examples of species distribution models are shown for different plants.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This document describes tools and methods for eco-geographical land characterization (ELC) mapping and characterization of plant genetic resource collecting sites. It discusses how ELC maps are developed by selecting important bioclimatic, geophysical, and edaphic variables through statistical analysis and clustering. It also describes how the Ecogeo tool can be used to characterize collecting sites based on geographic and environmental variables extracted from GIS data to build a characterization matrix for the sites.
Remotely sensed surface soil moisture data was assimilated into a soil moisture model to improve forecasts of global vegetation productivity. The assimilation significantly improved correlations between root-zone soil moisture estimates and vegetation index anomalies compared to the model alone, especially in data-poor regions prone to food insecurity. Future work will apply the method to SMOS surface soil moisture data to further enhance global vegetation productivity forecasting.
Predictive association between trait data and eco-geographic data for Nordic ...Dag Endresen
Scientific seminar with presentation of the FIGS method and results from the FIGS study with Nordic Barley landraces for the Vavilov Seminar at IPK Gatersleben (12 May 2010).
Endresen, D.T.F. (2010). Predictive association between trait data and ecogeographic data for Nordic barley landraces. Crop Sci. 50(6):2418-2430. doi: 10.2135/cropsci2010.03.0174
THEME – 2 Pattern and Climate Change-Induced Patterns and their Implications ...ICARDA
This document discusses patterns in plant biodiversity and genetics resources as they relate to climate change. It begins by reviewing how plant distribution patterns have historically been used to study species origins and evolution. It then examines current plant diversity patterns and how spatial variations exist in populations and ecosystems. Specific examples are given on cowpea distribution patterns in Africa and algorithms used to detect relationships between environments and traits. The document concludes by discussing how mathematical modeling can be used to capture shifts in traits and occurrences under future climate change.
Presentation by Avery Cohn, Maria Bowman, David Zilberman and Kate O’Neill, Workshop on Institutional arrangements for forest-agriculture boundaries, August 2011
TesTable and GEOQUAL are tools that evaluate the quality of passport data and geo-referencing for plant genetic resources. TesTable checks table formats for passport data and can report or correct errors. GEOQUAL assigns quality values to passport data coordinates based on parameters like coordinate accuracy, site description matching with administrative data, and environmental suitability of the collecting site. It summarizes these parameters to provide an overall quality score on a scale of 0-100. Evaluating geo-referencing quality helps ensure passport data supports the goals of conservation and use of plant genetic resources.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
This document describes tools and methods for eco-geographical land characterization (ELC) mapping and characterization of plant genetic resource collecting sites. It discusses how ELC maps are developed by selecting important bioclimatic, geophysical, and edaphic variables through statistical analysis and clustering. It also describes how the Ecogeo tool can be used to characterize collecting sites based on geographic and environmental variables extracted from GIS data to build a characterization matrix for the sites.
Remotely sensed surface soil moisture data was assimilated into a soil moisture model to improve forecasts of global vegetation productivity. The assimilation significantly improved correlations between root-zone soil moisture estimates and vegetation index anomalies compared to the model alone, especially in data-poor regions prone to food insecurity. Future work will apply the method to SMOS surface soil moisture data to further enhance global vegetation productivity forecasting.
Predictive association between trait data and eco-geographic data for Nordic ...Dag Endresen
Scientific seminar with presentation of the FIGS method and results from the FIGS study with Nordic Barley landraces for the Vavilov Seminar at IPK Gatersleben (12 May 2010).
Endresen, D.T.F. (2010). Predictive association between trait data and ecogeographic data for Nordic barley landraces. Crop Sci. 50(6):2418-2430. doi: 10.2135/cropsci2010.03.0174
THEME – 2 Pattern and Climate Change-Induced Patterns and their Implications ...ICARDA
This document discusses patterns in plant biodiversity and genetics resources as they relate to climate change. It begins by reviewing how plant distribution patterns have historically been used to study species origins and evolution. It then examines current plant diversity patterns and how spatial variations exist in populations and ecosystems. Specific examples are given on cowpea distribution patterns in Africa and algorithms used to detect relationships between environments and traits. The document concludes by discussing how mathematical modeling can be used to capture shifts in traits and occurrences under future climate change.
Presentation by Avery Cohn, Maria Bowman, David Zilberman and Kate O’Neill, Workshop on Institutional arrangements for forest-agriculture boundaries, August 2011
TesTable and GEOQUAL are tools that evaluate the quality of passport data and geo-referencing for plant genetic resources. TesTable checks table formats for passport data and can report or correct errors. GEOQUAL assigns quality values to passport data coordinates based on parameters like coordinate accuracy, site description matching with administrative data, and environmental suitability of the collecting site. It summarizes these parameters to provide an overall quality score on a scale of 0-100. Evaluating geo-referencing quality helps ensure passport data supports the goals of conservation and use of plant genetic resources.
Summer Allen
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
This document summarizes a project analyzing deforestation in the Amazon rainforest near Rio Branco, Brazil using satellite imagery from NASA and GIS software. The student acquired satellite images from 1990, 2000, and 2015, georeferenced and classified the images in ERDAS to identify forested, cleared, and built up areas, and calculated that 6.31% of vegetation was lost from 1990 to 2000. Based on past deforestation rates, the student predicts that without reforestation efforts, 40% of the forest could be lost by 2030 due to factors like population growth.
Jake Campolo
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
The document discusses the impacts of climate change on crop yields based on several studies. It finds that increases in temperature, dry periods, and extreme rainfall negatively affect crop yields. It then proposes using adaptation and mitigation strategies developed through modeling to address these impacts. Specifically, it suggests selecting climate change scenarios to simulate, developing a global crop response model, and conducting localized "virtual experiments" to identify adapted crop varieties and traits.
Belen Franch
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
Western crop science society of america conference oregon, 2013 - greensee...Wtarc Conrad Montana
This document summarizes a study evaluating sensor-based nitrogen recommendations for spring wheat in Montana. Two sensors, the GreenSeeker and Pocket Sensor, were used to measure normalized difference vegetation index (NDVI) values at five experimental sites in order to determine topdress nitrogen fertilizer rates. The results showed strong relationships between NDVI values from the two sensors and spring wheat grain yields. However, the sensor-based nitrogen recommendations did not consistently optimize yields and sometimes recommended excessive nitrogen rates. Total nitrogen applied was most strongly correlated with yield, indicating sensor-based rates may need improvement to optimize productivity and profits.
This study aimed to establish a supervised classification of global blue carbon mangrove ecosystems using remote sensing techniques. Four classification models were compared for two regions of interest: the Zambezi Delta and Rufiji River Delta. The models used different vegetation indices and were assessed against published classification maps for accuracy. The NDVI model achieved the highest accuracy for both regions at around 80-83%. However, all models overpredicted mangrove cover in non-mangrove areas, suggesting improvements are needed to better account for land cover variability. The study demonstrates the potential for remote sensing to map mangroves globally but highlights challenges in achieving high accuracy.
Parker, L. Navarro-Racines, C. Available data for crop modelling and applications using EcoCrop. Second training in Climate vulnerability analysis using the EcoCrop model, organized by Mozambique Institute of Agricultural Research (IIAM) and the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Speaker and mentor. August – September 2014, Maputo-Mozambique.
Climate Change and Future Food Security: The Impacts on root and Tuber CropsACDI/VOCA
Background: Climate Sensitivity of Agriculture
Importance or Root Crops to Jamaican Food Security
Estimating Yields (Manually)- Yield vs. Climate Dilemma
Methodology: Tools and Approaches
Results: Parameterization, Future Production under Climate Change
Conclusions: Climate Smart Implications & Main lessons learnt
Este documento describe las principales propiedades de las poblaciones, incluyendo el tamaño, densidad, patrón de distribución, y tasa de crecimiento. Explica que el tamaño es el número de organismos en una población, la densidad es el número de organismos por unidad de área, y el patrón de distribución puede ser agregado, aleatorio, o uniforme. También describe los parámetros demográficos como las tasas de natalidad, mortalidad, emigración e inmigración, y cómo esto afecta la
Introduction to SDM with Maxent JohannesS Signerjsigner
Este documento presenta Maxent, un modelo de distribución de especies basado en el principio de máxima entropía. Maxent solo requiere puntos de presencia de una especie y variables ambientales para generar mapas de distribución potencial. El documento explica cómo configurar y ejecutar Maxent, interpretar los resultados e implementar validación cruzada. También cubre cómo proyectar modelos a escenarios climáticos futuros para evaluar posibles cambios en la distribución de especies.
Conferencia pronunciada en el contexto del Seminario internacional "Corredores ecológicos y planificación espacial". Organizado por el Instituto Universitario de Urbanística de la Universidad de Valladolid, los días 22 y 23 de septiembre de 2016.
La dispersión permite el movimiento de individuos de una población a nuevos hábitats para asegurar la descendencia de las especies. Existen cuatro tipos principales de dispersión: anemocoria, hidrocoria, anemo-hidrocoria y zoocoria. Los patrones de dispersión incluyen uniforme, aleatorio y agrupado. La dispersión difiere de la migración en que es un movimiento más desordenado, no implica a toda la población, y no tiene un punto de destino definido.
El documento describe los diferentes climas y paisajes de España, incluyendo el clima mediterráneo seco, el interior continental suave y acusado, el subtropical marítimo, de montaña, mediterráneo suavizado, oceánico y oceánico de transición. Luego describe las distribuciones de especies como el haya, alcornoque, roble y encina en España, así como diferentes paisajes como la costa asturiana, rías, picos de Europa, sierra Nevada, gran canaria y sus características.
Este documento presenta información sobre la ecología de poblaciones. Explica diferentes patrones de disposición espacial de las poblaciones como la disposición agrupada, uniforme y al azar. También describe factores que regulan el tamaño de las poblaciones como la depredación, disponibilidad de espacio y factores climáticos. Finalmente, analiza la variabilidad genética dentro de las poblaciones y su importancia para la adaptación a diferentes ambientes.
El documento describe las propiedades de una población, incluyendo su tamaño, densidad, tasas de natalidad y mortalidad, y patrones de crecimiento. Explica que una población está compuesta por organismos de la misma especie que habitan en una zona geográfica, y que su tamaño y distribución están influenciados por factores como depredadores, competidores y condiciones ambientales.
Este documento describe los conceptos básicos de poblaciones y comunidades, incluyendo las propiedades de las poblaciones como el potencial biótico, la resistencia ambiental, los patrones de crecimiento y la capacidad de carga. También explica la dinámica de las poblaciones a través del crecimiento biológico, las estrategias r y K, y las interacciones entre poblaciones como el aislamiento, la territorialidad y la alelopatía. Finalmente, analiza la dispersión y distribución de las poblaciones.
Nivel medio superior, IV Semestre, Ecología. Bloque 1. Conocimientos Básicos de Ecología. Tema 1.4 Población. Libro: Ecología y Medio Ambiente (Alma Blanca Aguilar) Editorial Nueva Imagen
Andy J Value Of A Coordinate Montpellier Nov 2009CIAT
Presentation at TDWG 2009 in montpellier on the value of geographic coordinates for exploring agricultural biodiversity patterns, and influencing conservation policy.
Presentation made by Andy Jarvis from the Decision and Policy Analysis Program of the International Centre for Tropical Agriculture (CIAT). Delivered at the TDWG conference 2009 in Montpellier, France in November.
Crop wild relatives are an important source of genetic diversity for food crops. They can provide traits for increasing crop yields, quality, and stress tolerance. However, many crop wild relatives face threats from climate change and habitat loss that put their long-term survival at risk. A gap analysis was conducted to assess ex situ conservation collections and distribution models of crop wild relatives to determine priority areas for further collecting efforts to capture their remaining genetic diversity. Over 400 taxa were analyzed to identify high, medium, and low priority species for focus on filling conservation gaps.
Summer Allen
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
This document summarizes a project analyzing deforestation in the Amazon rainforest near Rio Branco, Brazil using satellite imagery from NASA and GIS software. The student acquired satellite images from 1990, 2000, and 2015, georeferenced and classified the images in ERDAS to identify forested, cleared, and built up areas, and calculated that 6.31% of vegetation was lost from 1990 to 2000. Based on past deforestation rates, the student predicts that without reforestation efforts, 40% of the forest could be lost by 2030 due to factors like population growth.
Jake Campolo
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
The document discusses the impacts of climate change on crop yields based on several studies. It finds that increases in temperature, dry periods, and extreme rainfall negatively affect crop yields. It then proposes using adaptation and mitigation strategies developed through modeling to address these impacts. Specifically, it suggests selecting climate change scenarios to simulate, developing a global crop response model, and conducting localized "virtual experiments" to identify adapted crop varieties and traits.
Belen Franch
WEBINAR
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT
Western crop science society of america conference oregon, 2013 - greensee...Wtarc Conrad Montana
This document summarizes a study evaluating sensor-based nitrogen recommendations for spring wheat in Montana. Two sensors, the GreenSeeker and Pocket Sensor, were used to measure normalized difference vegetation index (NDVI) values at five experimental sites in order to determine topdress nitrogen fertilizer rates. The results showed strong relationships between NDVI values from the two sensors and spring wheat grain yields. However, the sensor-based nitrogen recommendations did not consistently optimize yields and sometimes recommended excessive nitrogen rates. Total nitrogen applied was most strongly correlated with yield, indicating sensor-based rates may need improvement to optimize productivity and profits.
This study aimed to establish a supervised classification of global blue carbon mangrove ecosystems using remote sensing techniques. Four classification models were compared for two regions of interest: the Zambezi Delta and Rufiji River Delta. The models used different vegetation indices and were assessed against published classification maps for accuracy. The NDVI model achieved the highest accuracy for both regions at around 80-83%. However, all models overpredicted mangrove cover in non-mangrove areas, suggesting improvements are needed to better account for land cover variability. The study demonstrates the potential for remote sensing to map mangroves globally but highlights challenges in achieving high accuracy.
Parker, L. Navarro-Racines, C. Available data for crop modelling and applications using EcoCrop. Second training in Climate vulnerability analysis using the EcoCrop model, organized by Mozambique Institute of Agricultural Research (IIAM) and the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Speaker and mentor. August – September 2014, Maputo-Mozambique.
Climate Change and Future Food Security: The Impacts on root and Tuber CropsACDI/VOCA
Background: Climate Sensitivity of Agriculture
Importance or Root Crops to Jamaican Food Security
Estimating Yields (Manually)- Yield vs. Climate Dilemma
Methodology: Tools and Approaches
Results: Parameterization, Future Production under Climate Change
Conclusions: Climate Smart Implications & Main lessons learnt
Este documento describe las principales propiedades de las poblaciones, incluyendo el tamaño, densidad, patrón de distribución, y tasa de crecimiento. Explica que el tamaño es el número de organismos en una población, la densidad es el número de organismos por unidad de área, y el patrón de distribución puede ser agregado, aleatorio, o uniforme. También describe los parámetros demográficos como las tasas de natalidad, mortalidad, emigración e inmigración, y cómo esto afecta la
Introduction to SDM with Maxent JohannesS Signerjsigner
Este documento presenta Maxent, un modelo de distribución de especies basado en el principio de máxima entropía. Maxent solo requiere puntos de presencia de una especie y variables ambientales para generar mapas de distribución potencial. El documento explica cómo configurar y ejecutar Maxent, interpretar los resultados e implementar validación cruzada. También cubre cómo proyectar modelos a escenarios climáticos futuros para evaluar posibles cambios en la distribución de especies.
Conferencia pronunciada en el contexto del Seminario internacional "Corredores ecológicos y planificación espacial". Organizado por el Instituto Universitario de Urbanística de la Universidad de Valladolid, los días 22 y 23 de septiembre de 2016.
La dispersión permite el movimiento de individuos de una población a nuevos hábitats para asegurar la descendencia de las especies. Existen cuatro tipos principales de dispersión: anemocoria, hidrocoria, anemo-hidrocoria y zoocoria. Los patrones de dispersión incluyen uniforme, aleatorio y agrupado. La dispersión difiere de la migración en que es un movimiento más desordenado, no implica a toda la población, y no tiene un punto de destino definido.
El documento describe los diferentes climas y paisajes de España, incluyendo el clima mediterráneo seco, el interior continental suave y acusado, el subtropical marítimo, de montaña, mediterráneo suavizado, oceánico y oceánico de transición. Luego describe las distribuciones de especies como el haya, alcornoque, roble y encina en España, así como diferentes paisajes como la costa asturiana, rías, picos de Europa, sierra Nevada, gran canaria y sus características.
Este documento presenta información sobre la ecología de poblaciones. Explica diferentes patrones de disposición espacial de las poblaciones como la disposición agrupada, uniforme y al azar. También describe factores que regulan el tamaño de las poblaciones como la depredación, disponibilidad de espacio y factores climáticos. Finalmente, analiza la variabilidad genética dentro de las poblaciones y su importancia para la adaptación a diferentes ambientes.
El documento describe las propiedades de una población, incluyendo su tamaño, densidad, tasas de natalidad y mortalidad, y patrones de crecimiento. Explica que una población está compuesta por organismos de la misma especie que habitan en una zona geográfica, y que su tamaño y distribución están influenciados por factores como depredadores, competidores y condiciones ambientales.
Este documento describe los conceptos básicos de poblaciones y comunidades, incluyendo las propiedades de las poblaciones como el potencial biótico, la resistencia ambiental, los patrones de crecimiento y la capacidad de carga. También explica la dinámica de las poblaciones a través del crecimiento biológico, las estrategias r y K, y las interacciones entre poblaciones como el aislamiento, la territorialidad y la alelopatía. Finalmente, analiza la dispersión y distribución de las poblaciones.
Nivel medio superior, IV Semestre, Ecología. Bloque 1. Conocimientos Básicos de Ecología. Tema 1.4 Población. Libro: Ecología y Medio Ambiente (Alma Blanca Aguilar) Editorial Nueva Imagen
Andy J Value Of A Coordinate Montpellier Nov 2009CIAT
Presentation at TDWG 2009 in montpellier on the value of geographic coordinates for exploring agricultural biodiversity patterns, and influencing conservation policy.
Presentation made by Andy Jarvis from the Decision and Policy Analysis Program of the International Centre for Tropical Agriculture (CIAT). Delivered at the TDWG conference 2009 in Montpellier, France in November.
Crop wild relatives are an important source of genetic diversity for food crops. They can provide traits for increasing crop yields, quality, and stress tolerance. However, many crop wild relatives face threats from climate change and habitat loss that put their long-term survival at risk. A gap analysis was conducted to assess ex situ conservation collections and distribution models of crop wild relatives to determine priority areas for further collecting efforts to capture their remaining genetic diversity. Over 400 taxa were analyzed to identify high, medium, and low priority species for focus on filling conservation gaps.
This document discusses downloading data from public databases like GBIF and GENESYS. It provides examples of using GBIF and GENESYS to find and download occurrence record data for the species Phaseolus coccineus. The document emphasizes filtering search results and carefully selecting which data fields to download.
This document discusses crop wild relatives and the importance of their genetic resources. It notes that crop wild relatives can serve as a source of novel traits for crop improvement. They share a common ancestry with crops and their genes can be used in traditional breeding. However, many crop wild relatives face threats from climate change and land use changes. The document presents a methodology for analyzing gaps in crop wild relative collections. This involves determining priority taxa, sampling deficiencies, potential distributions, environmental coverage and gaps. The approach aims to prioritize geographic areas for further collecting of crop wild relatives.
The document provides a summary of activities in 2012 and plans for 2013 regarding the collection, conservation and use of crop wild relatives (CWR). It discusses (1) closing the global system project, ramping up the CWR project, and initiating CRP Genebanks in 2012; (2) progress made in 2012 including regeneration of accessions, safety duplication, evaluation projects and results; and (3) plans for 2013 including CWR research, collecting, prebreeding and evaluation, and increasing information sharing and use of CWR. The overall aim is to collect, conserve and utilize important CWR diversity to help crops adapt to climate change.
This document discusses gene discovery and applications in rice. It outlines a 5-point plan: [1] Using wild rice species to discover important genes; [2] Studying sterility genes and developing interspecific bridges; [3] Developing gene discovery resources like mutant libraries; [4] Applying gene discovery to selection for traits like virus resistance; and [5] Planned applications of new genomic tools. The overall goal is to leverage wild rice diversity and new technologies to accelerate rice breeding.
This document discusses gene discovery in rice and its applications. It outlines 5 main points:
1) Using wild rice species to discover important genes through introgressions and interspecific bridges.
2) Genes controlling sterility and developing interspecific bridges.
3) Gene discovery resources like mutant libraries and nested association mapping populations.
4) Applying gene discovery to rice breeding and selection, using RHBV resistance as an example.
5) Planned applications of new genomic tools.
This document summarizes approaches, resources and tools for gene discovery and breeding in rice. It discusses the use of introgressions from wild rice species, like Oryza glaberrima, to discover genes of importance for traits like yield, abiotic stress tolerance and disease resistance. It describes the development and use of nested association mapping (NAM) populations, chromosome segment substitution lines (CSSLs), and interspecific "iBridge" lines to overcome reproductive barriers for wider use of wild species diversity in rice breeding. Software, genetic maps, and populations involving multiple institutions are also summarized for integrating genetic and genomic approaches to gene discovery.
Partnering on crop wild relative research at three scales: commonalities for ...CWRofUS
The potential for crop wild relatives (CWR) to contribute to crop improvement is growing due to improvements in information on species and their diversity, advancements in breeding tools, and the growing need for exotic genetic diversity to address compounding agronomic challenges. As wild plants, CWR are subject to a myriad of human caused threats to natural ecosystems, and their representation ex situ is often far from comprehensive. Ex situ conservation of many of these wild plants is also technically challenging, particularly in an environment of insufficient resources. Enhancing conservation, availability, and access to CWR requires a spectrum of action spanning basic and applied research on wild species to inform on-the-ground collecting, ex situ maintenance, and germplasm utilization. The development of effective information channels and productive partnerships between diverse organizations are essential to the success of these actions. Here we report on a spectrum of CWR activities involving broad partnerships, at three levels: a) the collaborative compilation and distribution on over 5 million occurrence data records on the CWR of major food crops, b) the analysis of conservation concerns and genetic resources potential of the CWR of potato, sweetpotato, and pigeonpea, and c) ongoing efforts to map the diversity and conservation concerns for CWR in the USA. Although differing in scales and depth of collaborations, the success of these initiatives are largely due to commonalities in research orientation, e.g., inclusiveness, offering clear incentives for involvement, and service providing to the crop science community.
Partnering on CWR research at three scales: commonalities for successCWR Project
The potential for crop wild relatives (CWR) to contribute to crop improvement is growing due to improvements in information on species and their diversity, advancements in breeding tools, and the growing need for exotic genetic diversity to address compounding agronomic challenges. As wild plants, CWR are subject to a myriad of human caused threats to natural ecosystems, and their representation ex situ is often far from comprehensive. Ex situ conservation of many of these wild plants is also technically challenging, particularly in an environment of insufficient resources. Enhancing conservation, availability, and access to CWR requires a spectrum of action spanning basic and applied research on wild species to inform on-the-ground collecting, ex situ maintenance, and germplasm utilization. The development of effective information channels and productive partnerships between diverse organizations are essential to the success of these actions. Here we report on a spectrum of CWR activities involving broad partnerships, at three levels: a) the collaborative compilation and distribution on over 5 million occurrence data records on the CWR of major food crops, b) the analysis of conservation concerns and genetic resources potential of the CWR of potato, sweetpotato, and pigeonpea, and c) ongoing efforts to map the diversity and conservation concerns for CWR in the USA. Although differing in scales and depth of collaborations, the success of these initiatives are largely due to commonalities in research orientation, e.g., inclusiveness, offering clear incentives for involvement, and service providing to the crop science community.
Presentation made by Andy Jarvis in the Latin American Congress of Chemistry on 30th September 2010, in the symposium on Biodiversity and Ecosystems: the role of the chemical sciences.
The document summarizes objectives and activities from Tropical Legumes I and II projects. The projects aimed to improve productivity of tropical legumes through developing genomic resources, identifying molecular markers and genes for biotic and drought stress resistance. Key outputs included genomic resources, genetic stocks with traits introgressed, molecular markers, improved germplasm, trained scientists, and data management strategies. The projects collaborated with partners in Africa and South Asia to build breeding capacity and validate approaches in drought-prone environments.
This document discusses gap analysis, a tool used to assess crop genetic and geographical diversity. It allows identifying areas where species collections are lacking and prioritizing species and locations for future collection efforts. The process involves reviewing taxonomy, gathering data on species distributions and environments, and identifying gaps in ex situ conservation coverage. Taxa are then prioritized as high, medium, or low priority for conservation. Results are publicly available and include recommendations on priority taxa to collect, maps of collection locations, and methodology details.
PK14:Continental‐scale analysis of total soil biodiversity using molecular te...CSM _BGBD biodiversity
This document discusses using molecular techniques to conduct a continental-scale analysis of total soil biodiversity. Researchers will conduct a baseline survey of microbes and invertebrates in fertile and degraded soils across large regions using DNA sequencing. Over 200 soil samples from Africa will be analyzed to obtain thousands of sequences to allow for intensive community analysis of soil bacteria, archaea, and invertebrates. The goal is to link these results to the Global Digital Soil Map project to map soil health conditions in Sub-Saharan Africa.
Trait Mining, prediction of agricultural traits in plant genetic resources with ecological parameters. Focused Identification of Germplasm Strategy (FIGS). For the Vavilov seminars at the IPK Gatersleben 13th June 2007. Dag Endresen, Michael Mackay, Kenneth Street.
This document discusses the application of ecogeography in plant genetic resources. It defines ecogeography as the study of the adaptive scenario of an individual, population or species through analysis of biotic and abiotic factors that affect survival. It describes how geographical information systems (GIS) can be used to characterize plant collecting sites based on ecogeographical variables and identify potential applications of GIS in plant genetic resources, such as optimized germplasm collecting and identification of suitable areas for conservation. Finally, it lists activities that can be performed using GIS, such as determining the representativeness of ex-situ collections and identifying areas with high phenotypic or genotypic diversity.
This document discusses strategies to improve chickpea productivity in marginal environments in sub-Saharan Africa and South Asia. It outlines genomic and genetic resources developed, including reference sets, genetic maps, genome sequencing, and marker assays. It also describes trait mapping efforts identifying QTL for drought tolerance. Molecular breeding approaches like MABC, MARS, and genomic selection are discussed along with efforts to build capacity in national agricultural research systems in these regions.
Trait data mining using FIGS, seminar at Copenhagen University (27 May 2009)Dag Endresen
This document discusses strategies to improve the utilization of germplasm collections in seedbanks to increase genetic diversity in food crops. Scientists often need to screen smaller subsets of accessions for particular traits due to the large size of collections. The document proposes exploring climate data as a prediction model for pre-screening crop traits before full field trials in order to identify landraces with a higher probability of possessing interesting traits, which could reduce costs compared to large-scale field screening. It describes linking genebank accession and trait observation data to climate data from locations where landraces originated to build models predicting traits from climate variables.
Similar to Castaneda2009 Modelamiento Distribucion Especies (20)
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Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
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“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
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* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
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Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
2. Contenido
• Por qué modelar especies?
• Requisitos
• Software
• Usos
• Validación modelos
Distribución actual de Vasconcellea quercifolia en Bolivia Distribución potencial de Vasconcellea quercifolia en Bolivia Distribución potencial corregida de Vasconcellea quercifolia en Bolivia
4. Requisitos
Variables Registros
ambientales Georreferenciados
de la especie
Software
modelamiento
Procesamiento en
Software GIS
Modelo de
Dist. potencial
9. Registros especies
IABIN GBIF
– 4 redes temáticas con – 189.471.323 registros
vínculos a diversos biodiversidad (9 Nov
tipos de información 2009)
– Énfasis: América – Global
– Acceso libre al público – Acceso libre al público
http://www.iabin.net / http://www.gbif.org/
10. Registros especies
SINGER GapAnalysis
– Registros de – 13 acervos genéticos
accesiones en bancos (7 en camino)
de germoplasma del – Datos totalmente
CGIAR georreferenciados
– Acceso libre al público – Acceso libre al público
http://www.singer.cgiar.org/ http://gisweb.ciat.cgiar.org/gapanalysis/
11. Registros especies
Calidad de datos crucial!!
Ej.: Bases de datos GBIF
CURRENT STATUS OF
THE Plantae RECORDS
12. Registros especies
• How to make the terrestrial data reliable enough?
– Verify coordinates at different levels
• Are the records where they say they are?
• Are the records inside land areas (for terrestrial plant species only)
• Are all the records within the environmental niche of the taxon?
– Correct wrong references
– Add coordinates to those that do not have
– Cross-check with curators and feedback to the database
13. • Using a random sample of 950.000
occurrences with coordinates
14. • Are the records where they say they are?:
country-level verification
Records with null country: 58.051 6,11% of total
Records with incorrect country: 6.918 0,72% of total
Total excluded by country 64.969 6,83% of total
Records
mostly
located
Inaccuracies in
in country
coordinates
boundaries
15. • Are the terrestrial plant species in land?:
Coastal verification
Records in the ocean: 9.866 1,03% of total
Records near land (range 5km): 34.347 3,61% of total
Records outside of mask: 369 0,04% of total
Total excluded by mask 44.582 4.69% of total
Errors, and more errors
16. Not so bad at all… stats
• 44’706.505 plant records
• 33’340.008 (74,57%) with coordinates
• From those
– 88.5% are geographically correct at two levels
– 6.8% have null or incorrect country (incl. sea
plant species)
– 4.7% are near the coasts but not in-land
Summary of errors or misrepresented data
17. RESULTING DATABASE
TOTAL EVALUATED RECORDS: 950.000
Good records: 840.449 88.47% of total
23. Software
ANN - Artificial Neural Networks
AquaMaps
Bioclim
CSM - Climate Space Model
Envelope Score
Environmental Distance
GARP - Genetic Algorithm for Rule-set Production
GARP Best Subsets
SVM - Support Vector Machines
http://openmodeller.sourceforge.net/
25. How likely is geneflow from GM
crops to their wild relatives in
centres of origin and diversity?
Meike Andersson, Carmen de Vicente, Diego F. Alvarez, Andy Jarvis,
Glenn Hyman, Ehsan Dulloo
http://gisweb.ciat.cgiar.org/geneflow/
26. 1. Wheat
Study crops 2. Rice
3. Maize
4. Soybean
Criteria for selection 5. Barley
6. Sorghum
Global importance; 7. Finger Millet
Worldwide production area; 8. Pearl Millet
9. Cotton
Advancement of transgenic 10. Oilseed rape
technology; and 11. Common bean
Contribution to food security 12. Groundnut
(crop species listed in the 13. Cassava
14. Potato
Annex I of the ITPGRFA and 15. Oat
CGIAR mandate crops) 16. Chickpea
17. Cowpea
18. Sweet potato
19. Banana & plantain
20. Pigeon pea
27. Tool to visualize likelihood of gene flow and
introgression
Five categories:
Very high
High
Moderate
Low
Very low
28. Slide 27
ed1 Perhaps i can merge this slide with the barley one
Ehsan Dulloo, 3/27/2008
29. CASE STUDY
Barley
(Hordeum vulgare ssp. vulgare)
30. Barley (H. vulgare ssp. vulgare)
Biological information
Annual, cool season crop, highly autogamous (98%)
Seed dispersal: water, animals
Volunteers frequent, weedy, but not invasive
Pollen Flow
Mainly wind-pollinated, pollen viability a few hours
Outcrossing 50 m
GM technology
Transformation protocols available
GM traits: pest/disease; malting & brewing
Field trials in Australia, Canada, Finland, Germany,
Hungary, Iceland, N/Zealand, UK and USA
To date, no reported commercial production of GM barley
31. Barley
Wild relatives
30 annual species in 4 sections
Compatible wild relatives
Wild progenitor ssp. spontaneum
Closest wild relative: H. bulbosum
Most Hordeum have limited geographical
distribution
Some spp. widespread (H. bulbosum) and
weedy in many parts of the world (e.g., H.
murinum, H. marinum, and H. jubatum)
Hybridization potential
GP1: domesticated barley and its wild
ancestor H. vulgare ssp. spontaneum
GP2: H. bulbosum
GP3: all other Hordeum species
33. Barley: Management
recommendations
Barriers with male-sterile bait plants around the area planted with
barley to capture any escaped pollen; separation distance for seed
production:
• USA and Canada: 3 m; OECD and EU 25-50 m;
Control volunteer cereals through crop rotation; perform shallow tilling
of the soil surface several days post-harvest.
Special measures should be taken when transporting barley seeds to
avoid seed spill out of harvesting vehicles; control volunteer plants in
road sides
At regional scale, segregation of crop types may be implemented to
avoid contamination of seed production fields
34. Barley
Conclusions
Introgression within barley crop-wild-
weedy complex possible
Probability of introgression between
barley and H. bulbosum is low
Spontaneous hybridisation with other
wild relatives is unlikely
Research gaps
Dynamics of barley pollen flow;
frequencies of outcrossing at various
distances
37. GapAnalysis
13 crop genepools analyzed, 7 analyses in the pipeline
Recommendations on which taxa are priority to conserve
Maps indicating what and where to collect
Results publicly available at: http://gisweb.ciat.cgiar.org/GapAnalysis/
41. Modelos en acción!
• Identificación de vacíos de colección de bancos de
germoplasma
• Análisis de cambios de riqueza bajo diferentes
escenarios cambio climático
• Análisis estado de conservación y amenazas de
especies silvestres
• Identificación ambientes para la prueba de nuevos
materiales.
• Entre otros…
42. Validación modelos
• ¿Son las variables usadas para generar el modelo, las más
adecuadas?
Caso: Bertholletia excelsa
Climático Climático + Climático +
ecoregiones 1 suelos 1
Climático + Climático + Climático +
suelos 2 ecoregiones 2 ecoregiones 3
43. Validación modelos
• Parámetros estadísticos
– Area under the receiver Operating
Characteristic curve (AUC)
– Receiver Operating Characteristic curve
(ROC)
– Correlation (COR)
– Kappa
44. Validación modelos
• Modelo basado en conocimiento de expertos
• Validación y re-parametrización
• KMLs de Google Earth + plugin + encuesta electrónica