Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

BACKGROUND: Conserving 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 FINDINGS: We 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/SIGNIFICANCE: By 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

Group-dependent population-level responses: inside of the gas field.

<p>Marginal coefficient estimates ± 95% CL of selection for human disturbance (a), security cover (b), and road density (c) by female elk during 2006-2009 in Raton Basin, Colorado, USA. Day time results are displayed among maternal statuses for elk inside of the gas field.</p

Functional responses in resource selection by female elk.

<p>Selection for the human disturbance footprint (a), security cover inside of the gas field (b), and security cover outside of the gas field (c) change as a function of availability. Availability was calculated at the seasonal use area level and conditional coefficients were estimated from generalized linear random-effects resource selection models. Dashes (-) and dashed lines symbolize night-time resource selection, and circles (•) and solid lines symbolize day-time resource selection. Dashes and circles outlined by open circles (○) or boxes (□) indicate conditional estimates for field-observed parturient elk in 2008 and 2009.</p

Resource selection by Rocky Mountain elk during calving time; sample size and number of locations used in analyses.

a<p>Inside refers to areas within the gas field and outside refers to areas adjacent but external to the gas field. GAM-predicted parturient refers to female elk that we predicted to be parturient based on results of generalized additive modeling (GAM) of movement data. Field-observed refers to elk for which we observed behavior in the field to assess parturition status.</p><p>Total sample fitted with Global Positioning Systems collars was 25, 40, 50, and 50 in 2006, 2007, 2008, and 2009, respectively. Within-year deviation from the available sample arises from 3 sources: 1) some collared elk moved out of the study area during calving, 2) the GAM-predicted sample was nested within the total sample, and 3) some individuals occupied areas both inside and outside of the gas field.</p

Marginal coefficient estimates ([SE]) for two-level random-effects models of resource selection by Rocky Mountain elk during calving time (15 May - 1 July), 2006–2009.

<p>- Model failed to converge.</p

Movement in female ungulates during calving time.

<p>Generalized from the literature <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0014597#pone.0014597-Vore1" target="_blank">[34]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0014597#pone.0014597-Poole1" target="_blank">[35]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0014597#pone.0014597-Long1" target="_blank">[36]</a>, parturient females often will make long-distance movements associated with pre-parturient “restlessness” within days of parturition and then exhibit reduced movement associated with provisioning the neonate (a). This pattern may provide a quantifiable distinction between parturient and non-parturient females. Also shown (b) is parameterization (equivalent degrees of freedom) as a function of span based on generalized additive models of distance moved between consecutive locations in 103 female Rocky Mountain elk. Loess smoothing and automated calculation of degrees of freedom using the generalized cross validation method were specified.</p

Population-level responses: inside versus outside of the gas field.

<p>Marginal coefficient estimates ±95% CL of day-time (a) and night-time (b) selection for security cover, and day-time (c) and night-time (d) selection for elevation by female elk during 2006-2009 in Raton Basin, Colorado, USA. Inside refers to elk occupying an active gas field whereas outside refers to elk occupying adjacent undeveloped areas; maternal status is not considered (<i>i.e.</i>, all sample elk are grouped depending on whether they occurred inside versus outside of the gas field).</p

Assigning the relative probability of use throughout the landscape.

<p>Comparison of how the relative predicted probability of use was assigned throughout the landscape depending on whether RSF mapping was based on resource selection behavior among female elk that occupied a natural gas field (a) or occupied areas adjacent to but outside of a natural gas field (b). Maps depict day-time probability of use. Wells are depicted as black dots. Borders of wildlife areas managed by the state of Colorado are depicted in red. Probability of use is scaled from low to high with each of 5 ordinal bins representing quantiles of the total number of pixels (30-m resolution) comprising the area. Charts (c, d) display map validation with columns depicting the number of locations from an independent sample of elk that, when plotted on RSF maps (a, b), occurred within each ordinal bin. The black horizontal line depicts expectation if resources were selected at random. The map based on behavior inside of the gas field validated poorly (c; <i>χ</i>² = 577.46, <i>df</i> = 4, <i>p</i><0.001) relative to the map based on behavior outside of the gas field (d; <i>χ</i>² = 849.18, <i>df</i> = 4, <i>p</i><0.001) with the distribution of validation locations differing significantly from random in both cases. RSF maps (a, b) are based on all sample elk inside and outside of the gas field, respectively; not shown is the RSF map based on elk predicted to be parturient using generalized additive models.</p

Covariates used in random-effects resource selection models and their descriptions.

<p>Covariates used in random-effects resource selection models and their descriptions.</p