Data file for field and laboratory assays of web-building spiders

Excel file containing 5 sheets: (1) field data on spider webs collected in alfalfa in Lexington, Ky, in 2009, along with results of PCR gut-content assays, (2) sticky-trap data collected in the same location and year; (3) laboratory trials determining how many springtails encountered were consumed; and (4) laboratory feeding trials to determine retention times of springtail DNA in spider guts. Sheet (5) is a key

Appendix A. Modeling of capture–mark–recapture (CMR) data for joint detection-CMR modeling of occupancy and abundance.

Modeling of capture–mark–recapture (CMR) data for joint detection-CMR modeling of occupancy and abundance

Supplement 2. Python and WinBUGS model code for simulation study.

<h2>File List</h2><blockquote> <p><a href="bugs_sim.py">bugs_sim.py</a> -- Python code to simulate data for input into WINBUGS. Program calls WINBUGS in a DOS command and sends summary output to a storage file.</p> <p><a href="def_sim.py">def_sim.py</a> -- Python code (called by bugs_sim.py) specifying input parameters for simulations.</p> <p><a href="oarunscript.txt">oarunscript.txt</a> -- WINBUGS script file for batch execution.</p> <p><a href="oa_model.txt">oa_model.txt</a> -- WINBUGS model file for batch execution.</p> <p><a href="oa_data.txt">oa_data.txt</a> -- WINBUGS data file (replaced at each simulation iteration).</p> <p><a href="oa_inits.txt">oa_inits.txt</a> -- WINBUGS initial parameter value file (replaced at each simulation iteration).</p> </blockquote><h2>Description</h2><blockquote> <p>To execute program in WINDOWS operating systems, place all files in /Program Files/ WINBUGS14 and open the file "bugs_sim.py". This file references the "def_sim.py" and simulates data and initial values, replacing oa_data.txt and oa_intis.txt. The program then executes WINBUGS as a DOS command, with parameters contained in "oa_runscript.txt", using the simulated model specified in "oa_model.txt" and current data and initial values. Summary output is sent to two comma-delimited files: "sim_params.csv" and "sim_summary.csv", which keep track of parameter values and model estimates, respectively, for each simulation, and from which estimator performance (e.g., bias, MSE, and interval coverage) can be evaluated.</p> <p><i>Note</i>: Execution of "bugs_sim.py" and "def_sim.py" requires installation of Python; we recommend ActiveState ActivePython 2.5 (http://www.activestate.com), and numpy numeric Python (http://www.scipy.org/Download). Installation of pymc (http://pymc.googlecode.com/files/pymc-2.0.win32-py2.5.exe) is required to access the likelihood objects in "bugs_sim.py"; alternatively users may code their own likelihood functions directly in Python. </p> </blockquote