Variogram models reveal habitat gradients predicting patterns of territory occupancy and nest survival among vesper sparrows

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Abstract

Characterizing landscapes as gradients may help illuminate animal-habitat relationships that are either 1) masked by or 2) impractical to investigate using a purely patch-based perspective. Among other methods, variogram models may reveal these gradients in the environment by quantifying spatial dependence among point samples, yet few analyses of animal habitat relationships employing variograms have been undertaken. Using vegetation volume measurements from 4-m2 plots within breeding vesper sparrow Pooecetes gramineus territories, we calculated four territory-scale gradients: 1) mean volume, 2) standard deviation of volume, 3) nugget (a measure of fine-scale variation), and 4) range (an index of patch size). The first two gradients are more commonly employed in animal ecology while the second two were derived using variogram models and are infrequently employed. We next used these gradients in generalized linear models predicting territory occupancy and daily nest survival. We found overwhelming support for employing the range parameter and models indicated 1) birds selected areas with lower average vegetation volume and smaller patch sizes and 2) had lower rates of nest predation in areas with larger patch sizes. While these results indicate a pattern of non-ideal habitat selection, there was no indication that territories which experienced nest predation were selected disproportionately. Our results underscore the utility of 1) variograms among other methods for quantifying gradients in animal habitat and 2) variogram model parameters in investigating the habitat ecology of animals. © 2014 The Authors.

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Sadoti, G., Pollock, M. G., Vierling, K. T., Albright, T. P., & Strand, E. K. (2014). Variogram models reveal habitat gradients predicting patterns of territory occupancy and nest survival among vesper sparrows. Wildlife Biology, 20(2), 97–107. https://doi.org/10.2981/wlb.13056

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