Risky Business: Tradeoffs Between Nutrition, Toxicity, and Predation by a Specialist Mammalian Herbivore

Animals must balance many risks and rewards when using resources and selecting habitats. Understanding how animals make these choices requires elucidating the functional significance and interactions among habitat features. The criteria an animal uses to determine the functional quality of a resource may differ from those traditionally measured in surveys of habitat quality. Similarly, the relative value of a particular resource may vary with an animal’s physiology or behavior, or the unique combination of the resource’s characteristics. Previous studies have identified a number of specific individual, measurable, habitat parameters that influence habitat selection of a sagebrush specialist, the pygmy rabbit (Brachylagus idahoensis). We used a combination of those parameters to test the hypothesis that pygmy rabbits evaluate habitats differently based on their intended use of those habitats. We measured seven potentially toxic plant secondary metabolites (PSMs) and crude protein levels in sagebrush at and around pygmy rabbit burrows, in addition to the proximity of each plant to the burrow entrance and the concealment from aerial predators offered by each plant. We also quantified two distinct types of habitat use by pygmy rabbits by counting foraging bite marks and fecal pellets. We used model selection to determine which combinations of habitat parameters best predicted each type of use. In general, parameters representing food quality (e.g., PSMs and protein) best predicted foraging (bite marks) and parameters representing safety (e.g., concealment and distance to refuge) best predicted resting and digestion (fecal pellets). These results suggest that pygmy rabbits use different criteria when evaluating habitats for different potential uses. We also used captive feeding trials to evaluate the preference of pygmy rabbits and mountain cottontails (Sylvilagus nuttallii) for five single PSMs in sagebrush compared to a mixture of those same five PSMs. Pygmy rabbits generally showed little preference among single PSMs compared to mixed PSMs, whereas mountain cottontails—dietary generalists—exhibited strong preferences. These results suggest that specialists are better adapted to cope with both high concentrations of single PSMs and mixtures in the foods they regularly encounter than are generalists. We propose that preference for particular PSMs by an herbivore reflect faster detoxification capacity for that specific PSM. The particular parameters used by pygmy rabbits to evaluate their habitats and food resources are important to understand if sagebrush habitats are to be effectively assessed, conserved, managed, and restored. Furthermore, identifying preference for particular components of resources by animals and correlating them with diverse measurements of use may facilitate more nuanced descriptions of habitat selection across taxa

Preferences of Specialist and Generalist Mammalian Herbivores for Mixtures versus Individual Plant Secondary Metabolites

Herbivores that forage on chemically defended plants consume complex mixtures of plant secondary metabolites (PSMs). However, the mechanisms by which herbivores tolerate mixtures of PSMs are relatively poorly understood. As such, it remains difficult to predict how PSMs, singly or as complex mixtures, influence diet selection by herbivores. Although relative rates of detoxification of PSMs have been used to explain tolerance of PSMs by dietary specialist herbivores, few studies have used the rate of detoxification of individual PSMs to understand dietary preferences of individual herbivores for individual versus mixtures of PSMs. We coupled in vivo experiments using captive feeding trials with in vitro experiments using enzymatic detoxification assays to evaluate the dietary preferences and detoxification capacities of pygmy rabbits (Brachylagus idahoensis), dietary specialists on sagebrush (Artemisia spp.), and mountain cottontails (Sylvilagus nuttallii), dietary generalists. We compared preference for five single PSMs in sagebrush compared to a mixture containing those same five PSMs. We hypothesized that relative preference for individual PSMs would coincide with faster detoxification capacity for those PSMs by specialists and generalists. Pygmy rabbits generally showed little preference among individual PSMs compared to mixed PSMs, whereas mountain cottontails exhibited stronger preferences. Pygmy rabbits had faster detoxification capacities for all PSMs and consumed higher concentrations of individual PSMs versus a mixture than cottontails. However, detoxification capacity for an individual PSM did not generally coincide with preferences or avoidance of individual PSMs by either species. Cottontails avoided, but pygmy rabbits preferred, camphor, the PSM with the slowest detoxification rate by both species. Both species avoided β-pinene despite it having one of the fastest detoxification rate. Taken together our in vivo and in vitro results add to existing evidence that detoxification capacity is higher in dietary specialist than generalist herbivores. However, results also suggest that alternative mechanisms such as absorption and the pharmacological action of individual or mixtures of PSMs may play a role in determining preference of PSMs within herbivore species

Scaling Up Sagebrush Chemistry with Near-Infrared Spectroscopy and UAS-Acquired Hyperspectral Imagery

Sagebrush ecosystems (Artemisia spp.) face many threats including large wildfires and conversion to invasive annuals, and thus are the focus of intense restoration efforts across the western United States. Specific attention has been given to restoration of sagebrush systems for threatened herbivores, such as Greater Sage-Grouse (Centrocercus urophasianus) and pygmy rabbits (Brachylagus idahoensis), reliant on sagebrush as forage. Despite this, plant chemistry (e.g., crude protein, monoterpenes and phenolics) is rarely considered during reseeding efforts or when deciding which areas to conserve. Near-infrared spectroscopy (NIRS) has proven effective in predicting plant chemistry under laboratory conditions in a variety of ecosystems, including the sagebrush steppe. Our objectives were to demonstrate the scalability of these models from the laboratory to the field, and in the air with a hyperspectral sensor on an unoccupied aerial system (UAS). Sagebrush leaf samples were collected at a study site in eastern Idaho, USA. Plants were scanned with an ASD FieldSpec 4 spectroradiometer in the field and laboratory, and a subset of the same plants were imaged with a SteadiDrone Hexacopter UAS equipped with a Rikola hyperspectral sensor (HSI). All three sensors generated spectral patterns that were distinct among species and morphotypes of sagebrush at specific wavelengths. Lab-based NIRS was accurate for predicting crude protein and total monoterpenes (R2 = 0.7–0.8), but the same NIRS sensor in the field was unable to predict either crude protein or total monoterpenes (R2 \u3c 0.1). The hyperspectral sensor on the UAS was unable to predict most chemicals (R2 \u3c 0.2), likely due to a combination of too few bands in the Rikola HSI camera (16 bands), the range of wavelengths (500–900 nm), and small sample size of overlapping plants (n = 28–60). These results show both the potential for scaling NIRS from the lab to the field and the challenges in predicting complex plant chemistry with hyperspectral UAS. We conclude with recommendations for next steps in applying UAS to sagebrush ecosystems with a variety of new sensors

Fearscapes: Mapping Functional Properties of Cover for Prey with Terrestrial LiDAR

Heterogeneous vegetation structure can create a variable landscape of predation risk—a fearscape—that influences the use and selection of habitat by animals. Mapping the functional properties of vegetation that influence predation risk (e.g., concealment and visibility) across landscapes can be challenging. Traditional ground-based measures of predation risk are location specific and limited in spatial resolution. We demonstrate the benefits of terrestrial laser scanning (TLS) to map the properties of vegetation structure that shape fearscapes. We used TLS data to estimate the concealment of prey from multiple vantage points, representing predator sightlines, as well as the visibility of potential predators from the locations of prey. TLS provides a comprehensive data set that allows an exploration of how habitat changes may affect prey and predators. Together with other remotely sensed imagery, TLS could facilitate the scaling up of fearscape analyses to promote the management and restoration of landscapes

Near-Infrared Spectroscopy Aids Ecological Restoration by Classifying Variation of Taxonomy and Phenology of a Native Shrub

Plant communities are composed of complex phenotypes that not only differ among taxonomic groups and habitats but also change over time within a species. Restoration projects (e.g. translocations and reseeding) can introduce new functional variation in plants, which further diversifies phenotypes and complicates our ability to identify locally adaptive phenotypes for future restoration. Near-infrared spectroscopy (NIRS) offers one approach to detect the chemical phenotypes that differentiate plant species, populations, and phenological states of individual plants over time. We use sagebrush (Artemisia spp.) as a case study to test the accuracy by which NIRS can classify variation within taxonomy and phenology of a plant that is extensively managed and restored. Our results demonstrated that NIRS can accurately classify species of sagebrush within a study site (75–96%), populations of sagebrush within a subspecies (99%), annual phenology within a population (\u3e99%), and seasonal phenology within individual plants (\u3e97%). Low classification accuracy by NIRS in some sites may reflect heterogeneity associated with natural hybridization, translocation of nonlocal seed sources from past restoration, or complex gene-by-environment interactions. Advances in our ability to detect and interpret spectral signals from plants may improve both the selection of seed sources for targeted conservation and the capacity to monitor long-term changes in vegetation

Preferences of Specialist and Generalist Mammalian Herbivores for Mixtures Versus Individual Plant Secondary Metabolites

Herbivores that forage on chemically defended plants consume complex mixtures of plant secondary metabolites (PSMs). However, the mechanisms by which herbivores tolerate mixtures of PSMs are relatively poorly understood. As such, it remains difficult to predict how PSMs, singly or as complex mixtures, influence diet selection by herbivores. Although relative rates of detoxification of PSMs have been used to explain tolerance of PSMs by dietary specialist herbivores, few studies have used the rate of detoxification of individual PSMs to understand dietary preferences of individual herbivores for individual versus mixtures of PSMs. We coupled in vivo experiments using captive feeding trials with in vitro experiments using enzymatic detoxification assays to evaluate the dietary preferences and detoxification capacities of pygmy rabbits (Brachylagus idahoensis), dietary specialists on sagebrush (Artemisia spp.), and mountain cottontails (Sylvilagus nuttallii), dietary generalists. We compared preference for five single PSMs in sagebrush compared to a mixture containing those same five PSMs. We hypothesized that relative preference for individual PSMs would coincide with faster detoxification capacity for those PSMs by specialists and generalists. Pygmy rabbits generally showed little preference among individual PSMs compared to mixed PSMs, whereas mountain cottontails exhibited stronger preferences. Pygmy rabbits had faster detoxification capacities for all PSMs and consumed higher concentrations of individual PSMs versus a mixture than cottontails. However, detoxification capacity for an individual PSM did not generally coincide with preferences or avoidance of individual PSMs by either species. Cottontails avoided, but pygmy rabbits preferred, camphor, the PSM with the slowest detoxification rate by both species. Both species avoided β-pinene despite it having one of the fastest detoxification rate. Taken together our in vivo and in vitro results add to existing evidence that detoxification capacity is higher in dietary specialist than generalist herbivores. However, results also suggest that alternative mechanisms such as absorption and the pharmacological action of individual or mixtures of PSMs may play a role in determining preference of PSMs within herbivore species

Mapping Foodscapes and Sagebrush Morphotypes with Unmanned Aerial Systems for Multiple Herbivores

Context The amount and composition of phytochemicals in forage plants influences habitat quality for wild herbivores. However, evaluating forage quality at fine resolutions across broad spatial extents (i.e., foodscapes) is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging this gap in spatial scale. Objectives We evaluated the potential for UAS technology to accurately predict nutritional quality of sagebrush (Artemisia spp.) across landscapes. We mapped seasonal forage quality across two sites in Idaho, USA, with different mixtures of species but similar structural morphotypes of sagebrush. Methods We classified the sagebrush at both study sites using structural features of shrubs with object-based image analysis and machine learning and linked this classification to field measurements of phytochemicals to interpolate a foodscape for each phytochemical with regression kriging. We compared fine-scale landscape patterns of phytochemicals between sites and seasons. Results Classification accuracy for morphotypes was high at both study sites (81–87%). Forage quality was highly variable both within and among sagebrush morphotypes. Coumarins were the most accurately mapped (r2 = 0.57–0.81), whereas monoterpenes were the most variable and least explained. Patches with higher crude protein were larger and more connected in summer than in winter. Conclusions UAS allowed for a rapid collection of imagery for mapping foodscapes based on the phytochemical composition of sagebrush at fine scales but relatively broad extents. However, results suggest that a more advanced sensor (e.g., hyperspectral camera) is needed to map mixed species of sagebrush or to directly measure forage quality

Food Quality, Security, and Thermal Refuge Influence the Use of Microsites and Patches by Pygmy Rabbits (\u3ci\u3eBrachylagus idahoensis\u3c/i\u3e) Across Landscapes and Seasons

How intensely animals use habitat features depends on their functional properties (i.e., how the feature influences fitness) and the spatial and temporal scale considered. For herbivores, habitat use is expected to reflect the competing risks of starvation, predation, and thermal stress, but the relative influence of each functional property is expected to vary in space and time. We examined how a dietary and habitat specialist, the pygmy rabbit (Brachylagus idahoensis), used these functional properties of its sagebrush habitat—food quality, security, and thermal refuge—at two hierarchical spatial scales (microsite and patch) across two seasons (winter and summer). At the microsite and patch scales, we determined which plant functional traits predicted the number of bites (i.e., foraging) by pygmy rabbits and the number of their fecal pellets (i.e., general habitat use). Pygmy rabbits used microsites and patches more intensely that had higher crude protein and aerial concealment cover and were closer to burrows. Food quality was more influential when rabbits used microsites within patches. Security was more influential in winter than summer, and more at Cedar Gulch than Camas. However, the influence of functional properties depended on phytochemical and structural properties of sagebrush and was not spatiotemporally consistent. These results show function-dependent habitat use that varied according to specific activities by a central-place browsing herbivore. Making spatially explicit predictions of the relative value of habitat features that influence different types of habitat use (i.e., foraging, hiding, and thermoregulating) will improve how we predict patterns of habitat use by herbivores and how we monitor and manage functional traits within habitats for wildlife