"Recovery planning for threatened and endangered steelhead requires measurable, objective criteria for determining an acceptably low risk of extinction. Here we propose viability criteria for two levels of biological organization: individual populations, and groups of populations within the South-Central/Southern California Coast Steelhead Recovery Planning Domain. For populations, we adapt criteria commonly used by the IUCN (The World Conservation Union) for identifying at-risk species. For groups of populations we implement a diversity-based 'representation and redundancy rule, ' in which diversity includes both life-history diversity and biogeographic groupings of populations. The resulting criteria have the potential for straightforward assessment of the risks posed by evolutionary, demographic, environmental, and catastrophic factors; and are designed to use data that are readily collected. However, our prescriptive approach led to one criterion whose threshold could not yet be specified due to inadequate data, and others in which the simplicity of the criteria may render them inefficient for populations with stable run sizes or stable life-history polymorphisms. Both of these problems could likely be solved by directed programs of research and monitoring aimed at developing more efficient (but equally risk-averse) 'performance-based criteria.' Of particular utility would be data on the natural fluctuations of populations, research into the stabilizing influence of life-history polymorphisms, and research on the implications of drought, wildfires, and fluvial sediment regimes. Research on estuarine habitat could also yield useful information on the generality and reliability of its role as nursery habitat. Currently, risk assessment at the population level is not possible due to data deficiency, highlighting the need to implement a comprehensive effort to monitor run sizes, anadromous fractions, spawner densities and perhaps marine survival. Assessment at the group level indicates a priority for securing inland populations in the southern Coast Ranges and Transverse Ranges, and a need to maintain not just the fluvial-anadromous life-history form, but also lagoon-anadromous and freshwater-resident forms in each population"--Abstract.

We present the first quantitative representation of the intensity of Yellowstone National Park's surficial geothermal activity mapped continuously in space. A radiative thermal anomaly was remotely sensed throughout a 19,682-km2 landscape covering Yellowstone National Park in the northern Rocky Mountains, USA. The anomaly is the residual terrestrial emittance measured using the Landsat Enhanced Thematic Mapper after accounting for elevation and solar effects, and was hypothesized to be an estimator of a lower bound for geothermal heat flux (GHF). Continuous variations in the anomaly were measured ranging from 0 W m- 2 up to a maximum heat flux of at least 94 W m- 2 (at the 28.5 m pixel scale). An independent method was developed for measuring GHF at smaller scales, based on inversion of a snowpack simulation model, combined with field mapping of snow-free perimeters around selected geothermal features. These perimeters were assumed to be approximately isothermal, with a mean GHF estimated as the minimum heat flux required to ablate the simulated snowpack at that location on the day of field survey. The remotely sensed thermal anomaly correlated well (r = 0.82) with the snowpack-inversion measurements, and supported the hypothesis that the anomaly estimates a lower bound for GHF. These methods enable natural resource managers to identify, quantify and predict changes in heat flux over time in geothermally active areas. They also provide a quantitative basis for understanding the degree to which Yellowstone's famous wildlife herds are actually dependent on geothermal activity.--Abstract.

Throughout the world, fragmentation of landscapes by human activities has constrained the opportunity for large herbivores to migrate. Conflict between people and wildlife results when migrating animals transmit disease to livestock, damage property, and threaten human safety. Mitigating this conflict requires understanding the forces that shape migration patterns. Bison Bos bison migrating from Yellowstone National Park into the state of Montana during winter and spring concern ranchers on lands surrounding the park because bison can transmit brucellosis (Brucella abortus) to cattle. Migrations have been constrained, with bison being lethally removed or moved back into the park. We developed a state-space model to support decisions on bison management aimed at mitigating conflict with landowners outside the park. The model integrated recent GPS observations with 22 years (1990-2012) of aerial counts to forecast monthly distributions and identify factors driving migration. Wintering areas were located along decreasing elevation gradients, and bison accumulated in wintering areas prior to moving to areas progressively lower in elevation. Bison movements were affected by time since the onset of snowpack, snowpack magnitude, standing crop, and herd size. Migration pathways were increasingly used over time, suggesting that experience or learning influenced movements. To support adaptive management of Yellowstone bison, we forecast future movements to evaluate alternatives. Our approach of developing models capable of making explicit probabilistic forecasts of large herbivore movements and seasonal distributions is applicable to managing the migratory movements of large herbivores worldwide. These forecasts allow managers to develop and refine strategies in advance, and promote sound decision-making that reduces conflict as migratory animals come into contact with people.