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So I am trying to use the package ppmLasso to create species distribution models. Before I can run my models I need to put my environmental data into a data frame instead of as a raster. I have done the conversion using the following code for all the variables in the ClimateTreeStack Raster:

class : RasterStack

dimensions : 4746, 5858, 27802068, 6 (nrow, ncol, ncell, nlayers)

resolution : 0.008333333, 0.008333333 (x, y)

extent : 92.19167, 141.0083, -11, 28.55 (xmin, xmax, ymin, ymax)

coord. ref. : +proj=longlat +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +no_defs

names : bio_1, bio_2, bio_3, bio_12, bio_15, Allsea1

min values : -45, 45, 34, 581, 5, 0

max values : 289, 132, 96, 7008, 126, 89

bio1_FRAME<-as.data.frame(ClimateTreeStack$bio_1, xy=TRUE)

FrameOmit1<-na.omit(bio1_FRAME)

X<-FrameOmit1$x

Y<-FrameOmit1$y

BIO_1<-FrameOmit1$bio_1*

Which yields the following data frame:

head(frame)

X Y BIO_1 BIO_2 BIO_3 BIO_12 BIO_15 tree

1 97.55417 28.54583 8 114 44 698 85 8

2 97.56250 28.54583 -2 115 44 688 86 5

3 97.57083 28.54583 -1 115 44 688 86 1

4 97.55417 28.53750 2 115 44 692 86 4

5 97.56250 28.53750 2 115 44 692 86 5

6 97.57083 28.53750 11 114 44 703 86 4

I then try to use this environmental data frame but the ppmlasso package fails. I have figured out that an issue may be that the environmental data frame doesn't represent a true grid as seen using the diff() function:

varX = sort(unique(frame$X))

varY = sort(unique(frame$Y))

X.step = diff(varX)

Y.step = diff(varY)

table(X.step)

X.step

0.00833333333332575 0.00833333333333997 0.00833333333335418

           3177                2261                 419 

table(Y.step)

Y.step

0.00833333333332931 0.00833333333333286 0.00833333333333464 0.00833333333333641 0.00833333333333997

              1                4107                 110                 457                  60 

0.0250000000000057 0.05833333333333

   1                    1

When using the diff() function data appropriate for ppmlasso should look like this:

BM.X = sort(unique(BlueMountains$env$X))

BM.Y = sort(unique(BlueMountains$env$Y))

BM.X.step = diff(BM.X)

BM.Y.step = diff(BM.Y)

table(BM.X.step)

BM.X.step

0.5

200

table(BM.Y.step)

BM.Y.step

0.5

300

So I know what my problem probably is. But I do not know how to fix it. Can someone please suggest the easiest way to coerce my data frame (or raster) so that it has equal grid cells and can be run through ppmlasso?

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  • Try projecting the raster to an equal-area CRS before pulling location points out, perhaps?
    – obrl_soil
    Feb 23, 2017 at 8:33
  • How exactly does the package fail? If it indeed is due to the imprecision in some of the variables, then signif can be your friend.
    – whuber
    Feb 23, 2017 at 17:20
  • @obrl_soil : I tried that and it worked for the X values but not the Y values....I projected it to an equal-area CRS: "+proj=aea +lat_1=7 +lat_2=-32 +lat_0=-15 +lon_0=125 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs"
    – mlfp88
    Feb 24, 2017 at 0:05
  • @whuber: The process fails at the start....it just runs and runs and won't quite. I tried the signif but I still had the same issue.
    – mlfp88
    Feb 24, 2017 at 0:07
  • I am a PhD student trying to use the ppmlasso for my dissertation so I am under a time crunch and I am getting so frustrated....So I GREATLY appreciate any help and ideas.
    – mlfp88
    Feb 24, 2017 at 0:08

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