Known-fate/Nest-success model exercise

Mule Deer Example

This exercise is designed to show how to run program MARK to compute survival from 'known-fate' data.

Background

These data are from White and Garrott (1990) in which 120 mule deer fawns in Colorado were equipped with radiotransmitters and followed through winter. Sixty-one fawns were on a study area near an oil shale development ("treatment") and 59 were from areas removed from human activity. Four of the 61 "treatment" deer left the study area and are not included in the input data.

	Number Released	Alive	Dead	Other
Treatment	61	19	38	4
Control	59	21	38	0

Data input

Input data consists of summarized frequencies of encounter-histories. Encounter-history is distinguished here from capture-history by having two codes for each occasion - One for capture-status, and one for recapture-status. The possibilities here are: 11=captured and dead recovery, and 10=captured and not recovered as dead.

The example we'll use for this model contains 2 groups of animals: Treatment and Control. So, each encounter-history will have 2 frequencies following the encounter-history. The following is a sample MARK input file (knownfate.inp):

/* known fate example (pg 344) */
10 19 21   /* 19 treatment-alive, 21 control-alive*/;
11 38 38   /* 38 treatment-dead,  38 control-dead */;

Explanation: The '10 19 21' means that 19 animals from group 1 (treatment) and 21 animals from group 2 (control) were captured in time 1 and were not recovered as dead (ie. they survived). The '11 38 38' means that 38 animals from group 1 and 38 animals from group 2 were captured in time 1 and recovered as dead in time 2 (ie. they did not surive).

Here are the steps to run MARK on this input file:

Start MARK by clicking 'Start' button (lower left corner usually), 'Programs', 'MARK 4.3', then 'MARK'. Or, double-click the MARK icon on the desktop.

When the form appears, go to the 'File' menu and select 'New'.

A dialog window will appear where you can specify the data type, title, filename, and occasion. For this example, click 'Known fate' under 'Select Data Type'. Click in the textbox under 'Title for this set of data', and type:'known-fate model exercise'. Next, click the button labelled 'Click to select file'.

The program will present a dialog box asking for the name of the input file. Find the folder containing the sample input file (knownfate.inp), then click on the file (knownfate.inp), then click 'Open'.

Change the number of occasions to 1, and the number of groups to 2. Click the group names button and enter 'treatment' for the first group, and 'control' for the second, then close the window.

Click 'OK' and the program will create a database file containing the results for this data.

For the 'known-fate' models, there is only 1 parameter (for each group): survival (S). Once the database file is created, MARK will open one PIM window for you. Go to 'PIM', then select 'Open parameter index matrix', and click 'Select all' to open the other group's survival PIM.

For this example, we want to run a two models: One where the survival is the same for treatment and control, and one where survival is different. So, the first model to run will be one where S for group 1 is equal to S for group 2.

Start by clicking 'Window', then 'Tile' so all PIM windows are visible. Next, click on the window containing the PIM for group 2 S (labelled 'Survival parameter (S) for Group 2', then click the '-' button. Click the 'Close' button on each of the PIM windows.

Run this model by going to the 'Run' menu and clicking 'Current model'.

A dialog box will appear allowing you to enter a model name and other information. Enter 'S(.)' in the 'Model Name' textbox, click the 'List Data' checkbox, then click 'OK to Run'.

A dialog box will appear. Click 'Yes' to include the output from the model you just ran in the database file.

To view the parameter estimates for this model, click the fourth button from the left in the Browser Results window.

2nd model - S(group)

The second model to run is one where survial is different for treatment and control animals.

First, close any open MARK or NOTEPAD windows except for the MARK program window. Next, open the PIM windows, 'PIM', 'Open parameter index matrix', and click 'Select all'.

Make all PIM windows visible ('Window', 'Tile'), then click the '+' button in the 'Survival parameter for group 2' PIM window. Close all PIM windows.

Click 'Run', 'Current Model', and enter 'S(g)' for the model name.

Click 'OK to run, then 'Yes' when asked to append model results to the database file. Parameter estimates can be viewed by clicking the fourth button from the left in the 'Results Browser' window.

Program MARK is also capable of performing a 'Likelihood-Ratio' test between models. To do this, click 'Tests', then 'LR tests'. Click the 'Select all' button, then 'OK'. The results are automatically displayed in the notepad.

Click 'File', and 'Exit' to exit the program.

Nest Success Using MARK

Nest success data can be analyzed using MARK with a different input format. Input for program MARK consists of 5 numbers for each animal. The first number is the day the animal was initially found (1 for all in this example). The second number is the day the animal was last seen alive (59 for the first 3 animals). The third number is the day the animal was last seen-dead or alive (62 for the first three animals). The fourth number is a code for the ultimate fate of the animal (0=successful, 1=not successful), and the last number is the number of nests with this encounter history. The following is an input file for program MARK:

nest survival group=1;
1 59 62 1 3;
1 48 48 0 1;
1 37 37 0 1;
1 22 26 1 1;
1 22 24 1 1;
1 12 17 1 1;
1 27 32 1 1;
1 32 32 0 1;
1 45 51 1 1;
1 26 32 1 1;

This file has been saved as 'mayf3.inp'. We'll try running MARK to to compute survival rate estimates for these data.

First, start a new project (File/New), then select 'Nest survival' data type. Set the number of occasions to 62, enter a title and click 'OK'. The only parameters are the survival parmeters, and there isn't enough data to estimate all 62 survival rates, so go to the 'Initial' menu and select 'Initial/Constant'. Close the PIM window and run the model (name it 'S(.)'). View the model output, then click 'File/exit' to quit.