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The role of landscape features and density dependence in growth and fledging rates of Piping Plovers in North Dakota, USA

For species with precocial young, survival from hatching to fledging is a key factor influencing recruitment. Furthermore, growth rates of precocial chicks are an indicator of forage quality and habitat suitability of brood-rearing areas. We examined how growth and fledging rates of Piping Plover ( Charadrius melodus ) chicks were influenced by landscape features, such as hatchling density (hatchlings per hectare of remotely sensed habitat [H ha -1 ]), island vs. mainland, and wind fetch (exposure to waves) at 2-km segments (n ¼ 15) of Lake Sakakawea, North Dakota, during 2007–2008. Hatchling growth was comparable with published estimates for other habitats. Models for fledging rate (fledged young per segment) assuming density dependence had more support (wi ¼ 96%) than those assuming density independence (wi ¼ 4%). Density-dependent processes appeared to influence fledging rate only at densities .5 H ha -1 , which occurred in 19% of the segments we sampled. When areas with densities .5 H ha -1 were excluded, density-dependence and density-independence models were equally supported (wi ¼ 52% and 48%, respectively). Fledging rate declined as the wind fetch of a segment increased. Fledging rate on mainland shorelines was 4.3 times greater than that on islands. Previous work has indicated that plovers prefer islands for nesting, but our results suggest that this preference is not optimal and could lead to an ecological trap for chicks. While other researchers have found nesting-habitat requirements to be gravelly areas on exposed beaches without fine-grain substrates, our results suggest that chicks fledge at lower rates in these habitats. Thus, breeding plovers likely require complexes of these nesting habitats along with protected areas with fine, nutrient-rich substrate for foraging by hatchlings.

North Dakota

Evaluation of an elk detection probability model in the Black Hills, South Dakota

Since 1993, elk ( Cervus canadensis nelsoni ) abundance in the Black Hills of South Dakota has been estimated using a detection probability model previously developed in Idaho, though it is likely biased because of a failure to account for visibility biases under local conditions. To correct for this bias, we evaluated the current detection probability across the Black Hills during January and February 2009–2011 using radio-collared elk. We used logistic regression to evaluate topographic features, habitat characteristics, and group characteristics relative to their influence on detection probability of elk. Elk detection probability increased with less vegetation cover (%), increased group size, and more snow cover (%); overall detection probability was 0.60 (95% CI 0.52–0.68), with 91 of 152 elk groups detected. Predictive capability of the selected model was excellent (ROC = 0.807), and prediction accuracy ranged from 70.2% to 73.7%. Cross-validation of the selected model with other population estimation methods resulted in comparable estimates. Future applications of our model should be applied cautiously if characteristics of the area (e.g., vegetation cover >50%, snow cover >90%, group sizes >16 elk) differ notably from the range of variability in these factors under which the model was developed.

South Dakota