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DTSTART;TZID=Europe/London:20260408T150000
DTEND;TZID=Europe/London:20260408T193000
DTSTAMP:20260419T065234
CREATED:20260311T154427Z
LAST-MODIFIED:20260409T164831Z
UID:10000594-1775660400-1775676600@prstats.org
SUMMARY:Model Validation for Species Distribution and Ecological Niche Modelling (MVSD01)
DESCRIPTION:Delivered remotely (Portugal)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, September 22nd\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				How to build an ecological niche model – ENM? This course covers the fundamental theory and principal methodologies used to build Ecological Niche Models (ENMs). These models\, which may also be referred to as species distribution models (SDMs)\, habitat suitability models\, or climate envelope models\, represent empirical or mathematical approaches to understanding a species’ ecological niche. ENM techniques can be broadly categorised as mechanistic or correlative. They function by relating known species information (such as geographical locations or physiological data) with various types of ecogeographical variables\, including environmental (e.g.\, climate)\, topographical (e.g.\, elevation)\, and human factors. The ultimate goal is to identify the conditions and factors that limit and define the species’ niche. The increasing popularity of ENMs stems from their utility in making conservation planning and management more effective and efficient. \nBy the end of the course\, participants should be able to: \n\nCalculate ecological niche models and specie distribution models\nUnderstand their results\, as well as to choose and apply the correct.\nHow to choose the best methodology depending on the aim of their type of study and data.\n\n  \n			\n				\n				\n				\n				\n				Intended Audiences\n				\nAcademics and post-graduate students working on projects related to spatial data.\nStudents and researchers working on biogeography\, spatial ecology\, or related disciplines with experience in ecological niche models.\n\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+1) local time \nAvailability – 30 Places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English\n			\n				\n				\n				\n				\n				Teaching Format\n				The morning of the first day will be mainly theoretical. The following days will be mainly practical\, with some short theoretical presentations. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Attendees will learn to use modelling algorithms like Maxent\, Bioclim\, Domain\, and logistic regressions\, and R packages for computing ENMs like Dismo and Biomod2. Also\, students will learn to compare different ecological niche models using the Ecospat package. Data sets for computer practicals will be provided by the instructors\, but participants are welcome to bring their own data. In the final practical\, the students will run ENM with their own data or with a new dataset\, applying all the methods shown during the previous days.\n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of statistical and ecological concepts.\n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and the R statistical package is necessary. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstatistics.com).\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 22nd\n				Day 1 – Classes from 09:30 to 17:30 \n\nTopic 1: Introduction to ENM theory. Definition of ecological niche model; introduction to species ecological niche theory\, types of ecological niches\, types of ENM\, diagram BAM\, ENMs as approximations to species’ niches.\nTopic 2: ENM methods. Mechanistic and correlative models. Overlap Analysis\, Biomod\, Domain\, Habitat\, Distance of Mahalanobis\, ENFA\, Maxent\, Logistic regression\, Generalised Linear Models\, Generalised Additive Models\, Generalised Boosted Regression Models\, Random Forest\, Support Vector Machines\, Artificial Neural Network.\nTopic 3: Preparing variables and species data. Getting climatic data from WorldClim and species data from the Global Biodiversity Information Facility using the geodata package. Choosing environmental data sources\, downloading variables\, Clipping variables\, Aggregating variables\, checking pixel size\, checking raster limits\, checking NoData\, Correlating variables.\n\n			\n				\n				\n				\n				\n				Tuesday 23rd\n				Day 2 – Classes from 09:30 to 17:30 \n\nTopic 4: Guidelines to calculate ENM. Concepts of ecological niche and how they can be modelled; classes of correlative models; modelling software; selection of study area; data sources for species records and environmental variables; types of species records and their influence on correlative models; errors in species records; minimum number of species records and environmental variables; effects of prevalence\, sampling design\, biases\, and collinearity between variables; model calculation; model projection to different scenarios in time and space; ensemble modelling; model validation; classification\, discrimination and calibration metrics; calculation of null models; analysis of model results; and model thresholding.\nTopic 5: Modelling with the predicts package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n			\n				\n				\n				\n				\n				Wednesday 24th\n				Day 3 – Classes from 09:30 to 17:30 \n\nTopic 6: Applications of ENM. Ecological niche identification\, Identification of contact zones\, Integration with genetical data\, Species expansions\, Species invasions\, Dispersion hypotheses\, Species conservation status\, Prediction of future conservation problems\, Projection to future and past climate change scenarios\, Modelling past species\, Modelling species richness\, Road-kills\, Diseases\, Windmills\, Location of protected areas.\nTopic 7: Modelling with the biomod2 package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n			\n				\n				\n				\n				\n				Thursday 25th\n				Day 4 – Classes from 09:30 to 17:30 \n\nTopic 8: Modelling with Maxent. Formatting the data\, parameterising Maxent\, calculating the models\, evaluating the models\, projecting the models over time and space.\nTopic 9: Compare statistically two different ecological niche models using the R package ecospat.\n\n			\n				\n				\n				\n				\n				Friday 26th\n				Day 5 – Classes from 09:30 to 17:30 \n\nTopic 10: Run ecological niche models with your own data.\nTopic 11: Participants’ talks. Attendees will have the opportunity to present their own data and analyse which is the best way to successfully obtain an ENM.\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal website\nWork Webpage\nResearchGate\nGoogleScholar\n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)
URL:https://prstats.org/course/model-validation-for-species-distribution-and-ecological-niche-modelling-mvsd01/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2026/01/SDMS01-1.jpg
GEO:39.399872;-8.224454
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260407T153000
DTEND;TZID=Europe/London:20260407T193000
DTSTAMP:20260419T065234
CREATED:20260309T151706Z
LAST-MODIFIED:20260409T161424Z
UID:10000591-1775575800-1775590200@prstats.org
SUMMARY:Mechanistic Species Distribution Modelling / Ecological Niche Modelling with NicheMapR (MSDM01)
DESCRIPTION:Delivered remotely (Portugal)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, September 22nd\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				How to build an ecological niche model – ENM? This course covers the fundamental theory and principal methodologies used to build Ecological Niche Models (ENMs). These models\, which may also be referred to as species distribution models (SDMs)\, habitat suitability models\, or climate envelope models\, represent empirical or mathematical approaches to understanding a species’ ecological niche. ENM techniques can be broadly categorised as mechanistic or correlative. They function by relating known species information (such as geographical locations or physiological data) with various types of ecogeographical variables\, including environmental (e.g.\, climate)\, topographical (e.g.\, elevation)\, and human factors. The ultimate goal is to identify the conditions and factors that limit and define the species’ niche. The increasing popularity of ENMs stems from their utility in making conservation planning and management more effective and efficient. \nBy the end of the course\, participants should be able to: \n\nCalculate ecological niche models and specie distribution models\nUnderstand their results\, as well as to choose and apply the correct.\nHow to choose the best methodology depending on the aim of their type of study and data.\n\n  \n			\n				\n				\n				\n				\n				Intended Audiences\n				\nAcademics and post-graduate students working on projects related to spatial data.\nStudents and researchers working on biogeography\, spatial ecology\, or related disciplines with experience in ecological niche models.\n\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+1) local time \nAvailability – 30 Places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English\n			\n				\n				\n				\n				\n				Teaching Format\n				The morning of the first day will be mainly theoretical. The following days will be mainly practical\, with some short theoretical presentations. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Attendees will learn to use modelling algorithms like Maxent\, Bioclim\, Domain\, and logistic regressions\, and R packages for computing ENMs like Dismo and Biomod2. Also\, students will learn to compare different ecological niche models using the Ecospat package. Data sets for computer practicals will be provided by the instructors\, but participants are welcome to bring their own data. In the final practical\, the students will run ENM with their own data or with a new dataset\, applying all the methods shown during the previous days.\n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of statistical and ecological concepts.\n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and the R statistical package is necessary. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstatistics.com).\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 22nd\n				Day 1 – Classes from 09:30 to 17:30 \n\nTopic 1: Introduction to ENM theory. Definition of ecological niche model; introduction to species ecological niche theory\, types of ecological niches\, types of ENM\, diagram BAM\, ENMs as approximations to species’ niches.\nTopic 2: ENM methods. Mechanistic and correlative models. Overlap Analysis\, Biomod\, Domain\, Habitat\, Distance of Mahalanobis\, ENFA\, Maxent\, Logistic regression\, Generalised Linear Models\, Generalised Additive Models\, Generalised Boosted Regression Models\, Random Forest\, Support Vector Machines\, Artificial Neural Network.\nTopic 3: Preparing variables and species data. Getting climatic data from WorldClim and species data from the Global Biodiversity Information Facility using the geodata package. Choosing environmental data sources\, downloading variables\, Clipping variables\, Aggregating variables\, checking pixel size\, checking raster limits\, checking NoData\, Correlating variables.\n\n			\n				\n				\n				\n				\n				Tuesday 23rd\n				Day 2 – Classes from 09:30 to 17:30 \n\nTopic 4: Guidelines to calculate ENM. Concepts of ecological niche and how they can be modelled; classes of correlative models; modelling software; selection of study area; data sources for species records and environmental variables; types of species records and their influence on correlative models; errors in species records; minimum number of species records and environmental variables; effects of prevalence\, sampling design\, biases\, and collinearity between variables; model calculation; model projection to different scenarios in time and space; ensemble modelling; model validation; classification\, discrimination and calibration metrics; calculation of null models; analysis of model results; and model thresholding.\nTopic 5: Modelling with the predicts package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n			\n				\n				\n				\n				\n				Wednesday 24th\n				Day 3 – Classes from 09:30 to 17:30 \n\nTopic 6: Applications of ENM. Ecological niche identification\, Identification of contact zones\, Integration with genetical data\, Species expansions\, Species invasions\, Dispersion hypotheses\, Species conservation status\, Prediction of future conservation problems\, Projection to future and past climate change scenarios\, Modelling past species\, Modelling species richness\, Road-kills\, Diseases\, Windmills\, Location of protected areas.\nTopic 7: Modelling with the biomod2 package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n			\n				\n				\n				\n				\n				Thursday 25th\n				Day 4 – Classes from 09:30 to 17:30 \n\nTopic 8: Modelling with Maxent. Formatting the data\, parameterising Maxent\, calculating the models\, evaluating the models\, projecting the models over time and space.\nTopic 9: Compare statistically two different ecological niche models using the R package ecospat.\n\n			\n				\n				\n				\n				\n				Friday 26th\n				Day 5 – Classes from 09:30 to 17:30 \n\nTopic 10: Run ecological niche models with your own data.\nTopic 11: Participants’ talks. Attendees will have the opportunity to present their own data and analyse which is the best way to successfully obtain an ENM.\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal website\nWork Webpage\nResearchGate\nGoogleScholar\n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)
URL:https://prstats.org/course/mechanistic-species-distribution-modelling-ecological-niche-modelling-with-nichemapr-msdm01/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2026/01/SDMS01-1.jpg
GEO:39.399872;-8.224454
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251201
DTEND;VALUE=DATE:20251206
DTSTAMP:20260419T065234
CREATED:20230515T125812Z
LAST-MODIFIED:20260408T110433Z
UID:10000425-1764547200-1764979199@prstats.org
SUMMARY:Advanced Species Distribution Modelling (SDM's) and Ecological Niche Modelling (ENM's) (ASDM01)
DESCRIPTION:Delivered remotely (Portugal)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, December 1st\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you). \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				Have you built an Ecological Niche Model? If yes\, you have already encountered challenges on data preparation\, or have struggled with issues in models fitting and accuracy. This course will teach you how to overcome these challenges and improve the accuracy of your ecological niche models. By the end of 5-day practical course\, you will have the capacity to filter records and select your variables with variance inflation factor; to test effect of Maxent regularization parameter in models performance; to validate models performance and accuracy; to perform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”. \nEcological niche\, species distribution\, habitat distribution\, or climatic envelope models are different names for mechanistic and correlative models\, which are empirical or mathematical approaches to the ecological niche of a species. These methods relate different types of ecogeographical variables (environmental\, topographical\, human) to species physiological data or geographical locations\, in order to identify the factors limiting and defining the species&#39; niche. ENMs have become popular because of their efficiency in the design and implementation of conservation management. \nBy the end of 5-day practical course should be able to: \n\nfilter records and select your variables with variance inflation factor;\ntest the effect of Maxent regularization parameter in models performance;\nvalidate models performance and accuracy;\nperform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”.\n\nStudents will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Intended Audiences\n				This course is orientated to PhD and MSc students\, as well as other students and researchers working on biogeography\, spatial ecology\, or related disciplines\, with experience in ecological niche models. \n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+!) local time \nAvailability – 24 places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				The course will be mainly practical\, with some theoretical lectures. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Students will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of ecological niche models and biogeography in general is required\, thus we will assume the attendees know how to run an ecological niche model. \n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and R statistical package is necessary. It is also essential to have experience in ecological niche models. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstats.org). \n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n  \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 1st\n				Day 1 – Classes from 09:30 to 17:30 \n\nENM guide: how to model\nENM R packages.\nSources of environmental variables using geodata package.\nGetting species records with geodata package.\n\n			\n				\n				\n				\n				\n				Tuesday 2nd\n				Day 2 – Classes from 09:30 to 17:30 \n\nVariable selection with variance inflation factor (VIF) and usdm packages.\nChoosing the correct study area.\nFiltering records using usdm/spThin packages.\nChoosing pseudo-absences with Biomod2 package.\n\n			\n				\n				\n				\n				\n				Wednesday 3rd\n				Day 3 – Classes from 09:30 to 17:30 \n\nSplit records in training and test with ENMeval package.\nTest effect of Maxent regularization parameter.<.li>\nComparing correlative models with AIC\, with ENMeval package.\n\n			\n				\n				\n				\n				\n				Thursday 4th\n				Day 4 – Classes from 09:30 to 17:30 \n\nMESS practice with Biomod2 package.\nValidate models null models.\nVirtualSpecies virtualspecies packages.\n\n			\n				\n				\n				\n				\n				Friday 5th\n				Day 5 – Classes from 09:30 to 17:30 \n\nMechanistic model NicheMapper packages.\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal website \nWork Webpage \nResearchGate \nGoogleScholar \n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Salvador Arenas-Castro\n					\n					Dr. Salvador Arenas-Castro is a broad-spectrum ecologist with interesting in differentintegrative perspective of the fundamental ecology\, macroecology and biogeographywith their both application and relationship to climate and land management. He is alsoexploring other research sources in agroecology\, forestry\, spatial ecology\, andecoinformatics\, all addressed by explicitly considering the spatial component ofecological processes\, mainly applying spatially explicit modelling approaches\, GIS andremote sensing techniques. Please check his webpage for further information:https://salvadorarenascastro.wordpress.com \nGoogle Scholar: https://scholar.google.com/citations?user=UAYiB5UAAAAJ&hl=es&oi=aoResearchGate: https://www.researchgate.net/profile/Salvador-Arenas-Castro
URL:https://prstats.org/course/advanced-species-distribution-modelling-using-r-asdm01/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2023/05/ASDM01.jpg
GEO:39.399872;-8.224454
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250922
DTEND;VALUE=DATE:20250927
DTSTAMP:20260419T065234
CREATED:20220302T115332Z
LAST-MODIFIED:20260408T112046Z
UID:10000400-1758499200-1758931199@prstats.org
SUMMARY:Species Distribution Modelling (SDMs) and Ecological Niche Modelling (ENMs) (SDMR06)
DESCRIPTION:Delivered remotely (Portugal)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, September 22nd\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				How to build an ecological niche model – ENM? This course covers the fundamental theory and principal methodologies used to build Ecological Niche Models (ENMs). These models\, which may also be referred to as species distribution models (SDMs)\, habitat suitability models\, or climate envelope models\, represent empirical or mathematical approaches to understanding a species’ ecological niche. ENM techniques can be broadly categorised as mechanistic or correlative. They function by relating known species information (such as geographical locations or physiological data) with various types of ecogeographical variables\, including environmental (e.g.\, climate)\, topographical (e.g.\, elevation)\, and human factors. The ultimate goal is to identify the conditions and factors that limit and define the species’ niche. The increasing popularity of ENMs stems from their utility in making conservation planning and management more effective and efficient. \nBy the end of the course\, participants should be able to: \n\nCalculate ecological niche models and specie distribution models\nUnderstand their results\, as well as to choose and apply the correct.\nHow to choose the best methodology depending on the aim of their type of study and data.\n\n  \n			\n				\n				\n				\n				\n				Intended Audiences\n				\nAcademics and post-graduate students working on projects related to spatial data.\nStudents and researchers working on biogeography\, spatial ecology\, or related disciplines with experience in ecological niche models.\n\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+1) local time \nAvailability – 30 Places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English\n			\n				\n				\n				\n				\n				Teaching Format\n				The morning of the first day will be mainly theoretical. The following days will be mainly practical\, with some short theoretical presentations. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Attendees will learn to use modelling algorithms like Maxent\, Bioclim\, Domain\, and logistic regressions\, and R packages for computing ENMs like Dismo and Biomod2. Also\, students will learn to compare different ecological niche models using the Ecospat package. Data sets for computer practicals will be provided by the instructors\, but participants are welcome to bring their own data. In the final practical\, the students will run ENM with their own data or with a new dataset\, applying all the methods shown during the previous days. \n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of statistical and ecological concepts.\n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and the R statistical package is necessary. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstatistics.com).\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n \n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 22nd\n				Day 1 – Classes from 09:30 to 17:30 \n\nTopic 1: Introduction to ENM theory. Definition of ecological niche model; introduction to species ecological niche theory\, types of ecological niches\, types of ENM\, diagram BAM\, ENMs as approximations to species’ niches.\nTopic 2: ENM methods. Mechanistic and correlative models. Overlap Analysis\, Biomod\, Domain\, Habitat\, Distance of Mahalanobis\, ENFA\, Maxent\, Logistic regression\, Generalised Linear Models\, Generalised Additive Models\, Generalised Boosted Regression Models\, Random Forest\, Support Vector Machines\, Artificial Neural Network.\nTopic 3: Preparing variables and species data. Getting climatic data from WorldClim and species data from the Global Biodiversity Information Facility using the geodata package. Choosing environmental data sources\, downloading variables\, Clipping variables\, Aggregating variables\, checking pixel size\, checking raster limits\, checking NoData\, Correlating variables.\n\n			\n				\n				\n				\n				\n				Tuesday 23rd\n				Day 2 – Classes from 09:30 to 17:30 \n\nTopic 4: Guidelines to calculate ENM. Concepts of ecological niche and how they can be modelled; classes of correlative models; modelling software; selection of study area; data sources for species records and environmental variables; types of species records and their influence on correlative models; errors in species records; minimum number of species records and environmental variables; effects of prevalence\, sampling design\, biases\, and collinearity between variables; model calculation; model projection to different scenarios in time and space; ensemble modelling; model validation; classification\, discrimination and calibration metrics; calculation of null models; analysis of model results; and model thresholding.\nTopic 5: Modelling with the predicts package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n  \n			\n				\n				\n				\n				\n				Wednesday 24th\n				Day 3 – Classes from 09:30 to 17:30 \n\nTopic 6: Applications of ENM. Ecological niche identification\, Identification of contact zones\, Integration with genetical data\, Species expansions\, Species invasions\, Dispersion hypotheses\, Species conservation status\, Prediction of future conservation problems\, Projection to future and past climate change scenarios\, Modelling past species\, Modelling species richness\, Road-kills\, Diseases\, Windmills\, Location of protected areas.\nTopic 7: Modelling with the biomod2 package. Formatting the data\, parameterising the modelling correlative algorithms\, calculating the models\, evaluating the models\, projecting the models over time and space.\n\n			\n				\n				\n				\n				\n				Thursday 25th\n				Day 4 – Classes from 09:30 to 17:30 \n\nTopic 8: Modelling with Maxent. Formatting the data\, parameterising Maxent\, calculating the models\, evaluating the models\, projecting the models over time and space.\nTopic 9: Compare statistically two different ecological niche models using the R package ecospat.\n\n  \n			\n				\n				\n				\n				\n				Friday 26th\n				Day 5 – Classes from 09:30 to 17:30 \n\nTopic 10: Run ecological niche models with your own data.\nTopic 11: Participants’ talks. Attendees will have the opportunity to present their own data and analyse which is the best way to successfully obtain an ENM.\n\n  \n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal websiteWork WebpageResearchGateGoogleScholar \n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)
URL:https://prstats.org/course/species-distribution-modelling-sdmr06/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2022/03/SDMR06-1.jpg
GEO:39.399872;-8.224454
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