Spatially and temporally explicit environmental drivers of fawn recruitment in a native ungulate

Abstract

Recruitment is one of the fundamental drivers of ungulate population dynamics. Recruitment of neonates into an ungulate population can be influenced by a wide range of abiotic, biotic, and anthropogenic factors. Our objective was to examine which environmental variables most influenced pronghorn (Antilocapra americana) fawn recruitment, as measured by fawn:doe ratios, across six subpopulations in Idaho spanning 35 years (1984–2018) of herd composition surveys. Using a retrospective analysis, we examined the influence of precipitation, minimum and maximum temperatures, Palmer drought severity, normalized difference vegetation index (NDVI), vegetation, and elevation across five biological time periods of interest (one and two months pre‐parturition, one and two months post‐parturition, and breeding). Environmental factors, especially the variance in the greenness of vegetation (i.e., NDVI) during the two months post‐parturition (during lactation), were the main drivers of fawn recruitment for subpopulations occupying mountain valleys. Pronghorn fawn recruitment in these mountain valleys was dependent on the condition of the lactating female as influenced by the quality of vegetation, which would subsequently influence fawn growth rates. In contrast, pronghorn recruitment at lower elevations was driven by several environmental variables (i.e., NDVI, drought severity, minimum and maximum temperatures, forb, and grass cover) during the month pre‐parturition. Environmental variables at lower elevations were influencing the condition of the female during gestation which, if favorable, would result in higher birth weights and subsequent increased fawn survival. At intermediate elevation sites, results were mixed with fawn recruitment at one site influenced by low temperatures, which could induce hypothermia in fawns, while recruitment at the other site was influenced by drought severity during gestation (two months pre‐parturition). Influence of these environmental variables was also related to the timing of pronghorn arriving at the high elevation sites (i.e., arriving just prior to fawning); hence, effects were predominantly post‐parturition. In contrast, low elevation sites either had resident pronghorn or earlier arrival; thereby, effects on fawn recruitment were mostly from pre‐parturition variables. Given the range of environmental factors influencing pronghorn subpopulations, managers will need to consider the timing, intensity, and variability of environmental conditions as conditions were spatially and temporally explicit.

Temporal and Spatial Influences on Fawn Summer Survival in Pronghorn Populations: Management Implications from Noninvasive Monitoring

“…We attempted to delineate nonreproductive-aged (i.e., yearling) from reproductive-aged (i.e., ≥2 years) females during surveys to increase precision in our recruitment estimates [65]. Several years of these same surveys in various subpopulations of pronghorn were used to examine the influence of landscape variables and climate on fawn recruitment across Idaho [68].…”

“…Forb protein intake [62] and fawn recruitment estimates shared a similar pattern, indicating that increasing diet quality, or forbs, available to pronghorn may be a management strategy to increase fawn recruitment. The annual metabolic commitment that female pronghorn make to fawn recruitment and the influence of dietary nutritional quality on female condition [68] stresses the value of using adult female fecal nitrogen as a predictor of recruitment.…”

“…Advances in the GenBank software will increase the taxonomic resolution of plants consumed and highlight the temporal and spatial importance of particular plant species. Gese et al [68] explored environmental influence on pronghorn fawn recruitment in Idaho and found that the climatic drivers were spatially and temporarily explicit to the elevation each subpopulation occupied. Finally, our small sample size limited the statistical inferences that could be made on correlation results.…”