Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

Abstract

BackgroundConserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled.Methodology/Principal FindingsWe present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72–88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy.Conclusions/SignificanceBy directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action.

Winter Resource Selection by Mule Deer on the Wyoming–Colorado Border Prior to Wind Energy Development

“…This perceived risk is in addition to direct mortality associated with roads (i.e., deervehicle collisions). However, not all forms of anthropogenic features will be perceived as a risk, which depends on the type and level of human activity (Dzialak et al 2011a;Harju et al 2011). For example, some anthropogenic features such as homes can be an artificial refugium from hunting or natural predators.…”

“…Winter range typically provides food, cover, and protection from snow accumulation and adverse weather conditions (Mule Deer Working Group 2007). Important seasonal habitats, such as winter range, have the potential to influence population demographics such as survival and reproduction (Sawyer et al 2006;Dzialak et al 2011a). For example, winter range typically comprises a relatively small proportion of the total available range, which can result in deer congregating into smaller areas at greater densities (Mule Deer Working Group 2007).…”

“…The proposed development would include wind turbines and associated access roads and electrical collection lines. Recent work has addressed effects of natural gas and oil development on mule deer (Sawyer et al 2006 and elk (Dzialak et al 2011a(Dzialak et al , 2011bHarju et al 2011), but a paucity of data exists on the effects of wind energy development on large vertebrates. Much research has focused on avian species, but only one study to date has examined the potential influence of wind energy development on a large ungulate (i.e., elk in Oklahoma; Walter et al 2006).…”

Incorporating within- and between-patch resource selection in identification of critical habitat for brood-rearing greater sage-grouse

“…The estimated relative displacement index was one approach to incorporating information on behavior to strengthen inference on resource needs (Figures 1 and 2). Other approaches to identify behavioral modes or to assign data to defined modes have involved random walk models (Wu et al 2000), cluster analysis (Van Moorter et al 2010), state-space models (Jonsen et al 2005), fractals (Etzenhouser et al 1998;Webb et al 2009), and generalized additive models (Dzialak et al 2011a). Results of the resource Raster surfaces depicting encamped and traveling behavior of greater sage-grouse (Centrocercus urophasianus) in south-central Wyoming, USA, during 2009 to 2012 were developed with the predicted probability of occurrence classified into ten relative probability bins (1 = lowest, 10 = highest) that included 10% of the landscape area.…”

High-voltage power lines near wild reindeer calving areas

“…Successful calving in suitable habitats over generations is vital for sustainable populations of wild ungulates (Dzialak et al 2011). For alpine and arctic ungulates, optimal calving areas are generally thought to require low levels of anthropogenic disturbances and low predation risk, as well as early snow free patches offering fresh plant growth (Frid and Dill 2002;Skogland 1984; Van der Wal et al 2000;Wittmer et al 2006).…”