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Fig 1.

Map of California Gnatcatcher habitat in Ventura, Los Angeles, San Bernardino, Orange, Riverside, and San Diego counties as predicted by a habitat suitability model.

Sources: [21, 29, 30].

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Fig 1 Expand

Fig 2.

Distribution of California Gnatcatcher survey points at the regional scale in Ventura, Los Angeles, San Bernardino, Orange, Riverside, and San Diego counties, CA in 2016.

Sources: [2932].

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Fig 3.

Distribution of California Gnatcatcher survey points at the subregional scale in San Diego and Orange counties, CA in 2016.

Sources: [2932].

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Fig 4.

Distribution of California Gnatcatcher survey points by year of last fire in San Diego County, CA in 2016.

Sources: [2933].

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Table 1.

Vegetation species, heights, and unvegetated substrates recorded at California Gnatcatcher survey plots in 2016.

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Table 2.

Sample sizes for points surveyed and analyzed in 2015 and 2016 regional, subregional and postfire datasets.

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Fig 5.

Average percent cover (+ SD) of vegetation species and cover types at regional points, 2016.

See Table 2 for sample sizes.

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Fig 5 Expand

Fig 6.

Average percent cover (± SE) of vegetation and cover types at regional points occupied and not occupied by California Gnatcatchers, 2016.

See Table 2 for sample sizes.

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Fig 6 Expand

Fig 7.

Average percent cover (+ SD) of vegetation species and cover types at regional, San Diego (SD) subregional, and Orange County (OC) subregional points, 2016.

See Table 2 for sample sizes.

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Fig 7 Expand

Fig 8.

Average percent cover (± SE) of total shrubs and trees, and total herbaceous vegetation, across regional, San Diego (SD) subregional, and Orange County (OC) subregional points, 2016.

See Table 2 for sample sizes.

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Fig 8 Expand

Fig 9.

Average percent cover (+ SD) in 2016 of vegetation species and cover types at unburned points and points burned in 2003–06, 2007–10, and 2011–14.

See Table 2 for sample sizes.

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Fig 9 Expand

Fig 10.

Average percent cover (± SE) in 2016 of total shrubs and trees, and total herbaceous vegetation, across unburned points and points burned in 2003–06, 2007–10, and 2011–14.

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Fig 10 Expand

Table 3.

Variables with loadings > 0.35 on factors extracted by Principal Components Analysis of the regional, San Diego and Orange County subregional, and postfire (unburned) datasets for 2016.

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Table 3 Expand

Fig 11.

California Gnatcatcher occupancy in relation to cover of California sagebrush, California buckwheat, total shrub/tree (quadratic function), total herbaceous, time since last fire (quadratic function; plotted as year of last fire), and shrub height at regional points in 2016.

Gray lines represent 95% confidence interval. All covariates except shrub height from model 1; shrub height from model 2; Table 4).

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Fig 11 Expand

Table 4.

Logistic regression models of California Gnatcatcher occupancy in 2016 as a function of habitat covariates at the regional scale.

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Table 4 Expand

Fig 12.

California Gnatcatcher occupancy in relation to cover of California sagebrush, time since last fire (linear and quadratic functions; plotted as year of last fire), sunflowers, California buckwheat, and laurel sumac at San Diego subregional points in 2016.

Gray lines represent 95% confidence interval. California sagebrush from model 1, time since last fire from model 2, sunflowers from model 4, California buckwheat from model 5, and laurel sumac from model 7; Table 5).

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Fig 12 Expand

Fig 13.

California Gnatcatcher occupancy in relation to elevation at San Diego subregional points in 2016.

Gray lines represent 95% confidence interval. From model 6; Table 5).

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Fig 13 Expand

Table 5.

Logistic regression models of California Gnatcatcher occupancy in 2016 as a function of habitat covariates in the San Diego subregion.

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Fig 14.

California Gnatcatcher occupancy in relation to cover of California sagebrush, California buckwheat, sunflowers, and bare ground, and to elevation, at Orange County subregional points in 2016.

Gray lines represent 95% confidence interval. From model 1; Table 6).

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Fig 14 Expand

Table 6.

Logistic regression models of California Gnatcatcher occupancy in 2016 as a function of habitat covariates in the Orange County subregion.

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Table 6 Expand

Fig 15.

California Gnatcatcher occupancy in relation to cover of California sagebrush, laurel sumac, sage, sunflowers, and California buckwheat at unburned points in 2016.

Gray lines represent 95% confidence interval. California sagebrush, laurel sumac, sage, and sunflowers from model 1; California buckwheat from model 2; Table 7).

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Fig 15 Expand

Fig 16.

California Gnatcatcher occupancy in relation to cover of grass and other herbaceous at unburned points in 2016.

Gray lines represent 95% confidence interval. Grass from model 2; other herbaceous from model 3; Table 7).

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Fig 17.

California Gnatcatcher occupancy in relation to cover of California sagebrush in four postfire categories in 2016.

Gray lines represent 95% confidence interval. From model 1; Table 7).

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Table 7.

Logistic regression models of California Gnatcatcher occupancy in 2016 as a function of habitat covariates in postfire habitat.

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Table 8.

Comparison of covariates in best supported models (ΔAICc or ΔQAICc ≤ 2) predicting California Gnatcatcher occupancy in 2016 in the regional, San Diego (SD) subregional, Orange County (OC) subregional, and postfire datasets.

Effect of covariate: “+” = positive, “-”= negative, “+/-”= a threshold effect where the initial effect is positive, “-/+” = a threshold effect where the initial effect is negative. Asterisk means 95% confidence interval of the beta estimate for covariate does not include 0 in at least one model. Parentheses mean that ΔAICc or ΔQAICc > 2; see Tables 4 and 5.

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Fig 18.

Occupancy (± SE) of California Gnatcatchers at regional and subregional points in 2016.

Occupancy estimated as model-averaged occupancy across best supported models (ΔAICc or ΔQAICc ≤ 2) for each dataset; see Tables 46.

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Fig 19.

Occupancy (± SE) of California Gnatcatchers as a function of time since burn in 2015 and 2016.

Unburned points were not surveyed in 2015. Occupancy in 2015 estimated from model with constant occupancy and detection probabilities. Occupancy in 2016 estimated from model-averaged occupancy across best supported models (ΔAICc ≤ 2) for postfire dataset; see Table 7.

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