Publications by MD
Document
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 pred...
10736 sym R (27966 sym/97 pcs) 15 img
Connectivity_1
In today’s practical we will look at different conceptualizations of connectivity in ecology and explore two kinds of analysis of connectivity. 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 how species movement records can ...
11621 sym R (14704 sym/75 pcs) 17 img
SDM_2_PPM
In week 3 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 spatial...
22493 sym R (38757 sym/384 pcs) 25 img
Document
In week 3 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 spatial...
24135 sym R (46320 sym/408 pcs) 25 img
SDM_Two
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 spatial...
23121 sym R (42394 sym/538 pcs) 21 img
SDM Part One MD
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 ...
17095 sym R (27898 sym/120 pcs) 26 img
GEOG71922
In practical 2 of GEOG71922 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 ba...
16973 sym R (22710 sym/79 pcs) 10 img
GEOG70922W1
In the first practical for GEOG70922 we will familiarize ourselves with the R working environment and consider the effects of resolution, resampling and spatial data aggregation in our analysis. We looked at these ideas in the lecture and also briefly in GEOG60951. Here we will go into a little more depth and experiment with some simulated (or ...
13672 sym R (7973 sym/88 pcs) 16 img
Species Distribution Modelling Two
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 spatial...
23111 sym R (39714 sym/528 pcs) 21 img
SDM 2
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 spatial...
23093 sym R (41568 sym/510 pcs) 21 img