Publications by MD
GEOG70922 Easter Tips
Here I have put together a couple of tips to help get around some recent changes to packages used on the course that may be causing you some trouble. How to install older versions of R packages (or existing versions not supported by newer editions of R) Sometimes we want to install an older version of an R package. This might be to ensure repoduc...
3375 sym R (4042 sym/8 pcs) 3 img
GEOG70922 Week 9 Diversity
In this week’s practical we will consider two principal concerns in spatial ecology that we have looked at largely in isolation on this course: prediction and inference. Both of these analytical approaches are important in ecology and conservation science. From the perspective of biodiversity, the ability to interpret ecological data and predic...
10506 sym R (29215 sym/110 pcs) 15 img
GEOG70922 Connectivity Week 8
In today’s practical we will look at different conceptualizations of connectivity in ecology. We will explore two kinds of analysis of connectivity from this second perspective. We will take the example of least cost paths, revisiting some data that we created in Week 3, and that of network connectivity, drawing on graph theory to investigate h...
9377 sym R (13733 sym/82 pcs) 16 img
Week 7 Landscape Metrics
In this practical you will be guided through some spatial techniques for exploring basic concepts in landscape ecology. So far on the course we have been mainly focused on species ecology in that we have considered point data at the centre of our analysis. There are some broader ideas and approaches derived from the discipline of landscape ecolog...
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Species Distribution Modelling II
In week 4 we looked at the use of envelope models, general linear models, maxent and point process models for estimating species distribution (Bradypus variegatus). According to the cross-validation approach taken (K-fold partitioning) We achieved a good level of prediction. However, as we saw in the lecture, ecological data tend to be spatially ...
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GEOG70922 Week 5
In this week’s pratical we will take our first step into species distribution modelling. We will see that there are multiple options for modelling the distribution of species and that all depend on point data and the extraction of environmental factors to those points. First, let’s set the working directory and install the packages that we wi...
18112 sym R (20310 sym/99 pcs) 24 img
Meles
## Warning: package 'raster' was built under R version 3.6.2 ## Loading required package: sp ## Warning: package 'sp' was built under R version 3.6.2 ## Warning: package 'rgdal' was built under R version 3.6.2 ## rgdal: version: 1.4-8, (SVN revision 845) ## Geospatial Data Abstraction Library extensions to R successfully loaded ## Loaded GDAL...
6 sym R (891 sym/7 pcs)
Document
In today’s practical we will look at two spatially oriented and closely aligned areas of species ecology: range and resource selection. We will explore some of the ideas covered in the lecture using a telemetry dataset of Canis lupus (wolves) from a 2006 monitoring campaign in the Alberta region of Canada. We will use these data to explore opti...
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Week 2 Solution
setwd("P:/Week2") #Install packages install.packages(c("raster","dismo","sp","rgdal","mapview","ggplot2","cowplot","rgeos")) library(raster) library(rgdal) library(sp) sciurus<- read.csv("Sciurus.csv") head(sciurus) # view the first six rows of the data class(sciurus) #subset the data to only include points with complete coor...
5 sym R (8618 sym/3 pcs)
Scale Analysis
In practical 2 of GEOG71921 we will cover a range of spatial techniques in R that are central to working with spatial data in ecology. Today you will learn how to: 1) convert tabulated data to spatial point distributions, 2) crop data quickly and neatly to a desired study extent, 3) reclassify a raster for more focussed analysis, 4) provide backg...
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