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Supplementary Material

Response of lizard community structure to desert grassland restoration mediated by a keystone rodent

Bradley J. Cosentino, Robert L. Schooley, Brandon T. Bestelmeyer, and John Coffman

Corresponding Author: B.J. Cosentino, Department of Biology, Hobart and William Smith Colleges, Geneva, NY 14456, USA. e-mail: cosentino@hws.edu

Guide to Supplementary Material: Appendix A. Analysis of detection probability for lizards in southern New Mexico, USA. Appendix B. Comparison of mean (+ 1 SE) species richness, evenness, and diversity for lizards between areas treated with the herbicide tebuthiuron and untreated areas in southern New Mexico, USA.

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Appendix A Occupancy modeling was used to estimate the probability of detecting each lizard species at treated and untreated areas (n = 42). We used the program PRESENCE 3.1 to build single-season models of detection probability given detection histories that were based on repeated surveys for lizards at each area. Due to logistical constraints, areas could not be visited repeatedly over time. Repeated surveys consisted of surveys on the two transects within each area. Although space for time substitutions can lead to biased detection probabilities when a site is occupied by a species but not present at each sampling location (i.e., species availability; Kendall and White 2009), we believe bias associated with species availability was low given the large spatial extent of our sampling units (6 ha). The Akaike Information Criterion corrected for small sample size (AICC) was used to rank the support of two candidate models representing the effects of survey time and treatment (i.e., treatment versus reference) on detection probability for each species included in analyses: Time, Time + Treatment. The probability of occupancy was held constant for each model. Akaike weights (ωi) were calculated for each model, i, and we considered treatment type to have a strong effect on detection probability when 1) the "Time + Treatment" model was most supported, and 2) ΔAICC for the "Time" model was ≥ 2 (Burnham and Anderson 2002).

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Table A1. Models of detection probability for lizards in the southern New Mexico, USA. Main effects include survey time and treatment type (i.e., treated versus untreated area). Model statistics include the difference between model AICC and AICC for the best model (ΔAICC), Akaike weights (ωi), twice the negative log-likelihood (-2l), and the number of parameters estimated (K). Of the six species included in our analyses, only Aspidoscelis tesselata exhibited a significant difference in detection probability between treatment and untreated areas. Detection probability was greater on untreated areas than on treated areas for A. tesselata (beta estimate for the top model: Treatment = -2.51, SE = 1.10). Detection probability for A. uniparens was marginally greater on untreated areas than on treated areas (beta estimate for the top model: Treatment = -1.59, SE = 1.01). Species Model ΔAICC ωi -2l K Aspidoscelis inornata Time 0.00 0.66 52.21 3 Time + Treatment 1.36 0.34 51.12 4 Aspidoscelis tesselata Time + Treatment 0.00 0.86 78.58 4 Time 3.68 0.14 84.71 3 Aspidoscelis tigris Time 0 0.70 72.16 3 Time + Treatment 1.70 0.30 71.41 4 Aspidoscelis uniparens Time + Treatment 0.00 0.53 86.93 4 Time 0.21 0.47 89.59 3 Holbrookia maculata Time 0.00 0.77 66.90 3 Time + Treatment 2.42 0.23 66.87 4 Uta stansburiana Time 0.00 0.77 109.85 3 Time + Treatment 2.45 0.23 109.85 4

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Appendix B

Figure B1. Comparison of mean (+ 1 SE) species richness, evenness, and diversity for lizards between areas treated with the herbicide tebuthiuron and untreated areas in southern New Mexico, USA.

Richness Evenness Diversity

Value

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0.5

1.0

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2.5

3.0

UntreatedTreated