Landscape-Scale Conservation And Management Of Montane Wildlife: Contemporary Climate May Be Changing The Rules

Both paleontological and contemporary results have suggested that montane ecosystems to be systems of relatively rapid faunal change compared to many valley-bottom counterparts. In addition to experiencing greater magnitudes of contemporary change in climatic parameters than species in other ecosystems, mountain-dwelling wildlife must also accommodate often greater intra-annual swings in temperature and wind speeds, poorly developed soils, and generally harsher conditions. Research on a mountain-dwelling mammal species across 15 yrs of contemporary data and historical records from 1898-1956 suggest that pace of local extinctions and rate of upslope retraction have been markedly more rapid and governed by markedly different dynamics in the last decade than during the 20th century. This may mean that understanding past dynamics of species losses may not always help predict patterns of future loss. Given the importance of clinal variability and ecotypic variation, phenotypic plasticity, behavioral plasticity, and variation in climatic conditions, for widely-distributed species’ geographic ranges to be determined by different factors in different portions of their range is not uncommon. Consequently, greatest progress in understanding distributionalchange phenomena will occur with coordinated, landscape-scale research and monitoring. Landscape Conservation Cooperatives and Climate Science Centers are newly emerging efforts that may contribute greatly to such broad-scale investigations, e.g., climate-wildlife relationships. Based on our empirical findings and our review of related literature, we propose tenets that may serve as foundational starting points for mechanism-based research at broad scales to inform management and conservation of diverse montane wildlife and the ecosystem components with which they interact

Temporal vs. spatial variation in stress-associated metabolites within a population of climate-sensitive small mammals

Temporal variation in stress might signify changes in an animal&rsquo;s internal or external environment, while spatial variation instress might signify variation in the quality of the habitats that individual animals experience. Habitat-induced variationsin stress might be easiest to detect in highly territorial animals, and especially in species that do not take advantage ofcommon strategies for modulating habitat-induced stress, such as migration (escape in space) or hibernation (escape intime). Spatial and temporal variation in response to potential stressors has received little study in wild animals, especiallyat scales appropriate for relating stress to specific habitat characteristics. Here, we use the American pika (Ochotona princeps),a territorial small mammal, to investigate stress response within and among territories. For individually territorial animalssuch as pikas, differences in habitat quality should lead to differences in stress exhibited by territory owners. We indexedstress using stress-associated hormone metabolites in feces collected non-invasively from pika territories every 2 weeks fromJune to September 2018.We hypothesized that differences in territory qualitywould lead to spatial differences in mean stressand that seasonal variation in physiology or the physical environment would lead to synchronous variation across territoriesthrough time.We used linear mixed-effects models to explore spatiotemporal variation in stress using fixed effects of day-ofyearand broad habitat characteristics (elevation, aspect, site), aswell as local variation in habitat characteristics hypothesizedto affect territory quality for this saxicolous species (talus depth, clast size, available forage types). We found that temporalvariation within territories was greater than spatial variation among territories, suggesting that shared seasonal stressors aremore influential than differences in individual habitat quality. This approach could be used in other wildlife studies to refineour understanding of habitat quality and its effect on individual stress levels as a driver of population decline.</p

Managing for RADical ecosystem change: applying the Resist-Accept- Direct (RAD) framework

Ecosystem transformation involves the emergence of persistent ecological or social–ecological systems that diverge, dramatically and irreversibly, from prior ecosystem structure and function. Such transformations are occurring at increasing rates across the planet in response to changes in climate, land use, and other factors. Consequently, a dynamic view of ecosystem processes that accommodates rapid, irreversible change will be critical for effectively conserving fish, wildlife, and other natural resources, and maintaining ecosystem services. However, managing ecosystems toward states with novel structure and function is an inherently unpredictable and difficult task. Managers navigating ecosystem transformation can benefit from considering broader objectives, beyond a traditional focus on resisting ecosystem change, by also considering whether accepting inevitable change or directing it along some desirable pathway is more feasible (that is, practical and appropriate) under some circumstances (the RAD framework). By explicitly acknowledging transformation and implementing an iterative RAD approach, natural resource managers can be deliberate and strategic in addressing profound ecosystem change

Reimagining large river management using the Resist–Accept–Direct (RAD) framework in the Upper Mississippi River

Background: Large-river decision-makers are charged with maintaining diverse ecosystem services through unprecedented social-ecological transformations as climate change and other global stressors intensify. The interconnected, dendritic habitats of rivers, which often demarcate jurisdictional boundaries, generate complex management challenges. Here, we explore how the Resist–Accept–Direct (RAD) framework may enhance large-river management by promoting coordinated and deliberate responses to social-ecological trajectories of change. The RAD framework identifies the full decision space of potential management approaches, wherein managers may resist change to maintain historical conditions, accept change toward different conditions, or direct change to a specified future with novel conditions. In the Upper Mississippi River System, managers are facing social-ecological transformations from more frequent and extreme high-water events. We illustrate how RAD-informed basin-, reach-, and site-scale decisions could: (1) provide cross-spatial scale framing; (2) open the entire decision space of potential management approaches; and (3) enhance coordinated inter-jurisdictional management in response to the trajectory of the Upper Mississippi River hydrograph. Results: The RAD framework helps identify plausible long-term trajectories in different reaches (or subbasins) of the river and how the associated social-ecological transformations could be managed by altering site-scale conditions. Strategic reach-scale objectives may reprioritize how, where, and when site conditions could be altered to contribute to the basin goal, given the basin’s plausible trajectories of change (e.g., by coordinating action across sites to alter habitat connectivity, diversity, and redundancy in the river mosaic). Conclusions: When faced with long-term systemic transformations (e.g., \u3e 50 years), the RAD framework helps explicitly consider whether or when the basin vision or goals may no longer be achievable, and direct options may open yet unconsidered potential for the basin. Embedding the RAD framework in hierarchical decision-making clarifies that the selection of actions in space and time should be derived from basin-wide goals and reach-scale objectives to ensure that site-scale actions contribute effectively to the larger river habitat mosaic. Embedding the RAD framework in large-river decisions can provide the necessary conduit to link flexibility and innovation at the site scale with stability at larger scales for adaptive governance of changing social-ecological systems

Severity-adjusted evaluation of liver transplantation on health outcomes in urea cycle disorders

Purpose: Liver transplantation (LTx) is performed in individuals with urea cycle disorders when medical management (MM) insufficiently prevents the occurrence of hyperammonemic events. However, there is a paucity of systematic analyses on the effects of LTx on health-related outcome parameters compared to individuals with comparable severity who are medically managed. Methods: We investigated the effects of LTx and MM on validated health-related outcome parameters, including the metabolic disease course, linear growth, and neurocognitive outcomes. Individuals were stratified into “severe” and “attenuated” categories based on the genotype-specific and validated in vitro enzyme activity. Results: LTx enabled metabolic stability by prevention of further hyperammonemic events after transplantation and was associated with a more favorable growth outcome compared with individuals remaining under MM. However, neurocognitive outcome in individuals with LTx did not differ from the medically managed counterparts as reflected by the frequency of motor abnormality and cognitive standard deviation score at last observation. Conclusion: Whereas LTx enabled metabolic stability without further need of protein restriction or nitrogen-scavenging therapy and was associated with a more favorable growth outcome, LTx—as currently performed—was not associated with improved neurocognitive outcomes compared with long-term MM in the investigated urea cycle disorders.</p

Relating sub-surface ice features to physiological stress in a climate sensitive mammal, the American pika (Ochotona princeps).

The American pika (Ochotona princeps) is considered a sentinel species for detecting ecological effects of climate change. Pikas are declining within a large portion of their range, and ongoing research suggests loss of sub-surface ice as a mechanism. However, no studies have demonstrated physiological responses of pikas to sub-surface ice features. Here we present the first analysis of physiological stress in pikas living in and adjacent to habitats underlain by ice. Fresh fecal samples were collected non-invasively from two adjacent sites in the Rocky Mountains (one with sub-surface ice and one without) and analyzed for glucocorticoid metabolites (GCM). We also measured sub-surface microclimates in each habitat. Results indicate lower GCM concentration in sites with sub-surface ice, suggesting that pikas are less stressed in favorable microclimates resulting from sub-surface ice features. GCM response was well predicted by habitat characteristics associated with sub-surface ice features, such as lower mean summer temperatures. These results suggest that pikas inhabiting areas without sub-surface ice features are experiencing higher levels of physiological stress and may be more susceptible to changing climates. Although post-deposition environmental effects can confound analyses based on fecal GCM, we found no evidence for such effects in this study. Sub-surface ice features are key to water cycling and storage and will likely represent an increasingly important component of water resources in a warming climate. Fecal samples collected from additional watersheds as part of current pika monitoring programs could be used to further characterize relationships between pika stress and sub-surface ice features

Thermal summaries of temperature variables related to heat stress.

<p>Values obtained from sub-surface data loggers placed at Green Lakes Valley Watershed (GLVW) and Niwot Ridge LTER (NWT) during 2011–2013. Boxes depict medians and 25% and 75% quartiles. Whiskers extend through the 95% interquartile range. AST (Average Summer Temperature; Fig. A) corresponds to average temperature during June-September. SUMDTR (Summer Diurnal Temperature Range; Fig. B) corresponds to average diurnal temperature range June-September.</p

Relative support for predictors of pika stress.

<p>Akaike weights were calculated across all possible linear mixed models of data from both study sites, where each model included only direct effects based on 1–5 of the 5 predictor variables.</p><p>Relative support for predictors of pika stress.</p

Relative support for models of pika stress (GCM concentration) in the Green Lakes Valley Watershed.

<p>Models are ranked in order of increasing AIC values (Akaike’s information criterion). L denotes likelihood. ΔAIC is the difference between the indicated model and the best model (the model with lowest AIC). Unsupported models (ΔAIC > 4) are not shown. Marginal R² represents the amount of variance explained by fixed effects alone, while conditional R² represents the amount of variance explained by fixed and random effects in combination.</p><p>Relative support for models of pika stress (GCM concentration) in the Green Lakes Valley Watershed.</p

Relative support for models of pika stress (GCM concentration) across both study sites (Green Lakes Valley Watershed and Niwot Ridge LTER).

<p>Definitions are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119327#pone.0119327.t002" target="_blank">Table 2</a>.</p><p>Relative support for models of pika stress (GCM concentration) across both study sites (Green Lakes Valley Watershed and Niwot Ridge LTER).</p