Species Distribution&Env Niche Modelling  

Species distribution modelling and environmental niche modelling are types of modelling where the occurrence or absence of certain species or crops are linked to environmental conditions that are relevant. The type of organism that is modeled can be variable in nature, ranging from the presence of rare and endangered species, to the outbreak of pest species. It is used to make interpolations of observations of species over space using relevant explanatory variables. These extrapolations can be used to assess how likely the occurrence of such an species is in unvisited areas. Also, it can provide insight to what extent the spatial distribution of a species will change as a result of changes in conditions, for example due to land cover change, or climate change. Extrapolations are based on fitting an empirical relation between the presence or absence of a species and the environmental conditions under which it occurs, it’s “niche”. In this course students will learn hands on how to design, create and evaluate different kinds of environmental niche models (such as logistic regression, boosted regression trees and maximum entropy) and you will learn how you can use these models to make projections when conditions change. The course is of interest to people that need statistical interpolation techniques. Also, the course will teach you to apply different types of software packages. Next to geo-information software you will be working with the R-software. This course mainly aims at applications in the domain of natural resources, but when you have an interest in in other domains where this can be applied (e.g. disease outbreaks or rare events such as landslides) this course can also be very useful for you and there will be room to explore the application to your area of interest.
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2023-07-06T22:00:00Z
The first part of the course (60%) will be face-to-face teaching and supervised practical’s to acquire knowledge on relevant theories and learn how to apply these in a practical way. This will be assessed in a written test, and partly by the individual project making up. In the second part of the course, two small projects (one individual and one group) will train the student to place the learned techniques and theories into context. This will be student centered learning. The student has a choice of the type of species and or environment that wil be modellend. Also, the student has a choice in a type if (mini) research question that will be addressed in the mini project. The individual project (25%) tests the ability to create and evaluate ENM’s for a specific case study of interest for the student. In the group project (15%), the use of ENMs has to be placed in the context of Essential Biodiversity Variables (EBVs), sustainable agricultural, semi-natural and protected area landscapes, or information needs for policy applications (SDGs, Aichi targets). In the group, model outputs created in the individual project will be used as input for the evaluation how these can be used in either of these contexts.
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GIS and Remote sensing skills Basic understanding of regressionBasic understanding of inferential statistics (ANOVA, T test etc),GIS and Remote sensing skills Basic understanding of regression Basic understanding of inferential statistics (ANOVA, T test etc)
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201800300
Species Distribution & Environmental Niche Modelling
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UNIVERSITY OF TWENTE

Faculty of Geo-Information Science and Earth Observation