spatial analysis of roadkills along the Trans-Canada Highway in Banff National

Park. Here is a long overdue summary of the responses I received.

Question:

Hi I am working on a research project that studies roadkills on the Trans-Canada

Highway, a linear vector spanning over 141 miles. I am looking at hotspots, or

clusters of roadkills along the highway, from small to large mammals. I am

starting with a simple analysis that looks if the kills are related to the

access points, (breaks in the wildlife fence). Firstly, I was wondering if

someone knows a script that I can use that puts random points on my linear

vector, so I can look at a Chi-square test or Hines test for randomness. (Do I

need random points along the line vector or would a ploygon suffice?) Also once

I have tested for clusters, or aggregation, how do I link these clusters to the

access points. I am looking at a simple two step analysis, for testing for

clusters, and are these clusters related to the access points. It would be

great if someone could lead me in the right direction..............

Thanks Kari

Response 1:

You might want to look at "local statistics" and K functions. The journal

Geographical Analysis

has a number of articles on the subject.

Art Getis

Response 2:

1. If you will test against differences between two distributions, then both

your distributions must be comparable. Therefore you need random points on your

linerar vector.

2. Is the highway absolutely linear like a line between two points? In this

case you can use a simple worksheet function for random number generation like

in Excel. For testing you should only compare the coordinates of one axis

(west-east or north-south), its useful to choose the axis with the greatest

extend.

3. If the highway is not absolutely linear you can make a workaround. First

you should make a buffer around your highway with a very small distance/radius.

After buffering use a random number generator for polygons. For ArcView exists

a simple script, which you can find on the ESRI-Website: http://www.esri.com

Because the lateral extension of the buffer is very small I think you can

neglect it in all cases where you will find very great differences between both

the distributions. For testing you should only compare the coordiantes of one

axis (west-east or south-north), its useful to choose the axis with the greatest

extend.

4. To link the clusters with your access points you can go in different ways.

For instance you can make buffers with a defined radius around your access

points and do an identity operation. You will find some tools in Atlas*GIS

(access points) or ArcView (XTools-Extension, Animal Movement Extension; both

you can find on ESRI's site). I think the Animal Movement Extension is very

useful for your aims.

5. I think the best way to compare your distributions is to perform a

nearest-neighborhood analysis between your access points and the road kills

compared with the nearest neighborhood distances between your access points and

the random points.

hope this helps

Reinhard

Dr. Reinhard Klenke

Society for Nature Conservation and Landscape Ecology (GNL)

phone 49-39822-20 474

fax: 49-39822-20 474

Response 3:

Hi Kari,

I'm not really an expert in spatial statitics but it seem to me that you might

apply the Ripley's K statisitcs to your data. I recomment you to take a look

athe following article:

O'Driscoll, R.L. 1998. Description of spatial pattern in seabird distributions

along line transects using neighbour K statistics. Mar. Ecol. Prog. Ser.

165:81-94.

Also Boots, B.R. and A. Getis. 1988. Point Pattern Analysis. SAGE publications.

give some examples of the application of measures of dispersion in one

dimension. As for the software, well the only one I know is available is the

S-plus and you have to add the libraries Splancs and Spatial. THere is a

student version of S-plus for a little less than $100 dollars and libraries can

be downloaded from the internet. However, I am not sure if you can use the

software for one dimentsion directly, most likely you might need to make some

modifications and obviously you will need to study the S-plus language for that.

Anyway, hope this informations is of some help to you. Good luck,

Jose Alcantara

School of Forestry, Wildlife and Fisheries

Louisiana State University

Baton Rouge, La.

Response 4:

First of all numbers from a uniform (0,1) random number generator can be mapped

onto any stretch of highway. With as many points from the random generator as

there are road kills you can then create two empirical distributions and test

for their being the same with the Kolmogorov-Smirnov statistic. This will

simply tell you that the road kills are (not) from a uniform distribution along

the highway.

You actually do not have to generate the points. The cumulative distribution

along the highway has a slope of 1/L, where L is the length of the highway

segment. i.e. F=x/L, 0<=x<=L. Now make an empirical distribution of the

roadkills and use the K-S one sample test statistic.

You may also look at gap sizes and their distribution to obtain a 'best' Pearson

type distribution for waitng times, except your waiting time is simply the

distance between kills.

You may also divide the road into a set of segments and fill in the counts for a

one dimensional contingency table.

Lastly, you can use the scan statistic found in CLUSTER, CLUSTER can be

downloaded from CDC/ATSDR.

Send me your data, and I will find an unwilling student to have a look at them.

I wrote CLUSTER along with three others.

Sincerely yours,

Wanzer Drane

Professor of Biostatistics

USC School of Public Health, 205

Columbia, SC 29208

803-777-5053

Response 5:

Which software are you using for the analysis? I can give you some hints on

Avenue (ArcVIew script language) and S+, although I have no premade script.

Shouldn't be too difficult, though.

You can just transform all your observation in distances from the starting point

in the hwy, and then you just have to draw a random number.

BTW, where on the Hwy are you working? Is it the Banff stretch?

Marco Albani

PhD Candidate

Dept. of Forest Sciences - UBC

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