Predicting diet quality and genetic diversity of a desert-adapted ungulate with NDVI

Diet quality influences ungulate population dynamics but is difficult to measure at fine temporal or spatial resolution using field-intensive methods such as fecal nitrogen (FN). Increasingly, the remotely sensed vegetation index NDVI is used to represent potential ungulate diet quality, but NDVI's relationship with diet quality has yet to be examined for herbivores in desert environments. We evaluated how strongly NDVI was associated with diet quality of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert using FN data from multiple years and populations. We considered effects of temporal resolution, geographic variability, and NDVI spatial summary statistic on the NDVI-diet quality relationship. NDVI was more reliably associated with diet quality over the entire growing season than with instantaneous diet quality for a population. NDVI was also positively associated with population genetic diversity, a proxy for long-term, population-level effects of diet quality. We conclude that NDVI is a useful diet quality indicator for Mojave Desert bighorn sheep and potentially other desert ungulates. However, it may not reliably track diet quality if NDVI data are too spatially coarse to detect microhabitats providing high-quality forage, or if diet is strongly influenced by forage items that are weakly correlated with landscape greenness.Keywords: Bighorn sheep, Mojave Desert, Forage, Fecal nitrogenKeywords: Bighorn sheep, Mojave Desert, Forage, Fecal nitroge

Using network theory to prioritize management in a desert bighorn sheep metapopulation

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.Keywords: Gene flow, Colonization, Connectivity, Dispersal, Graph theory, Extinction, Habitat patch, Fragmented population, Landscape resistanc

Wave patterns generated by an axisymmetric obstacle in a two-layer flow

Gravity waves generated by a moving obstacle in a two-layer stratified fluid are investigated. The experimental configuration is three-dimensional with an axisymmetric obstacle which is towed in one of the two layers. The experimental method used in the present study is based on a stereoscopic technique allowing the 3D reconstruction of the interface between the two layers. Investigation into the wave pattern as a function of the Froude number, Fr, based on the relative density of the fluid layers and the velocity of the towed obstacle is presented. Specific attention is paid to the transcritical regime for which Fr is close to one. Potential energy trapped in the wave field patterns is also extracted from the experimental results and is analyzed as a function of both the Froude number, Fr, and the transcritical similarity parameter Γ. In particular, a remarkable increase in the potential energy around Fr = 1 is observed and a scaling allowing to assemble data resulting from different experimental parameters is proposed

Free surface flow past topography : a beyond-all-orders approach

The problem of steady subcritical free surface flow past a submerged inclined step is considered. The asymptotic limit of small Froude number is treated, with particular emphasis on the effect that changing the angle of the step face has on the surface waves. As demonstrated by Chapman & Vanden-Broeck (2006), the divergence of a power series expansion in powers of the square of the Froude number is caused by singularities in the analytic continuation of the free surface; for an inclined step, these singularities may correspond to either the corners or stagnation points of the step, or both, depending on the angle of incline. Stokes lines emanate from these singularities, and exponentially small waves are switched on at the point the Stokes lines intersect with the free surface. Our results suggest that for a certain range of step angles, two wavetrains are switched on, but the exponentially subdominant one is switched on first, leading to an intermediate wavetrain not previously noted. We extend these ideas to the problem of flow over a submerged bump or trench, again with inclined sides. This time there may be two, three or four active Stokes lines, depending on the inclination angles. We demonstrate how to construct a base topography such that wave contributions from separate Stokes lines are of equal magnitude but opposite phase, thus cancelling out. Our asymptotic results are complemented by numerical solutions to the fully nonlinear equations

CreechPredictingDietQualitySupplement.pdf

Diet quality influences ungulate population dynamics but is difficult to measure at fine temporal or spatial resolution using field-intensive methods such as fecal nitrogen (FN). Increasingly, the remotely sensed vegetation index NDVI is used to represent potential ungulate diet quality, but NDVI's relationship with diet quality has yet to be examined for herbivores in desert environments. We evaluated how strongly NDVI was associated with diet quality of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert using FN data from multiple years and populations. We considered effects of temporal resolution, geographic variability, and NDVI spatial summary statistic on the NDVI-diet quality relationship. NDVI was more reliably associated with diet quality over the entire growing season than with instantaneous diet quality for a population. NDVI was also positively associated with population genetic diversity, a proxy for long-term, population-level effects of diet quality. We conclude that NDVI is a useful diet quality indicator for Mojave Desert bighorn sheep and potentially other desert ungulates. However, it may not reliably track diet quality if NDVI data are too spatially coarse to detect microhabitats providing high-quality forage, or if diet is strongly influenced by forage items that are weakly correlated with landscape greenness.Keywords: Mojave Desert, Fecal nitrogen, Forage, Bighorn shee

CreechTylerFisheriesWildlifeUsingNetworkTheory_SupplementaryMaterial.pdf

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.Keywords: Landscape resistance, Dispersal, Habitat patch, Graph theory, Fragmented population, Connectivity, Gene flow, Extinction, Colonizatio