Antiferromagnetic spin phase transition in nuclear matter with effective Gogny interaction

The possibility of ferromagnetic and antiferromagnetic phase transitions in symmetric nuclear matter is analyzed within the framework of a Fermi liquid theory with the effective Gogny interaction. It is shown that at some critical density nuclear matter with D1S effective force undergoes a phase transition to the antiferromagnetic spin state (the opposite direction of neutron and proton spins). The self--consistent equations of spin polarized nuclear matter with D1S force have no solutions, corresponding to the ferromagnetic spin ordering (the same direction of neutron and proton spins) and, hence, the ferromagnetic transition does not appear. The dependence of antiferromagnetic spin polarization parameter as a function of density is found at zero temperature.Comment: Report at the workshop "Hot points in astrophysics and cosmology", Dubna, August, 2-13, 2004. REVTeX4, 9 pages, 3 figure

Spin polarized states in strongly asymmetric nuclear matter

In the framework of a Fermi liquid theory it is considered the possibility of appearance of spin polarized states in strongly asymmetric nuclear matter with Skyrme effective interaction. The zero temperature dependence of neutron and proton spin polarization parameters as functions of density is found for SLy4, SLy5 effective forces. It is shown that at some critical density it will be formed the state with the oppositely directed spins of neutrons and protons, while the state with the same direction of spins does not appear. In comparison with neutron matter, even small admixture of protons strongly decreases the threshold density of spin instability. It is clarified that protons become totally polarized within very narrow density domain while in the density profile of neutron spin polarization parameter their appear long tails near the transition density.Comment: Prepared with RevTeX4, 8p., 3 figures; to appear in PR

Incorporating Ecohydrologic Variables into Modeling of Patterns of Montane-Mammal Distribution and Abundance

Montane ecosystems have been suggested by both paleontological and contemporary research to often be systems of relatively rapid faunal change, compared to many valley-bottom counterparts. In addition to often (but not always) 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. We present new results of ecoregional level analyses of American pikas (Ochotona princeps Richardson) that illustrate how biologically relevant derived hydrological variables can be important to predictors of abundance. We also present new results from the Northern Rocky Mountains that illustrate how behavioral plasticity can, in at least some cases, ‘soften’ the boundaries of species’ bioclimatic niches. Landscape Conservation Cooperatives and Climate Science Centers are newly emerging efforts that may contribute greatly to broad-scale, mechanism-based investigations to inform management and conservation of diverse montane wildlife and the ecosystem components with which they interact. Based on our empirical findings and our review of the literature, we propose tenets that may serves as foundational starting points for our expanding research on montane animals across the Northern Rocky Mountain Region

Should we use climate analogs to predict climate impacts? A contemporary validation.

There is a need for location-specific, fine-grain, climate impact information to inform regional and local-level climate adaptation. However, such climate information is hard to obtain from the existing models either due to the lack of sufficient data or too coarse of a model output to be useful. Analog impact models (AIMs), provide an alternative approach. AIMs rely on climate analogs (locations in space and time that have similar climate) to forecast future climate impacts at a spatial grain as fine as a four kilometer pixel. Analog impact models assume that locations with equivalent climate (climate analogs) also share other important characteristics, such as vegetation type, primary productivity, disturbance regimes, etc. AIMs provide spatially resolved, fine grain predictions of climate impacts, which have the potential to inform location-specific climate adaptation. The use of AIMs is growing, yet there is a lack of information on the quality of AIM predictions. Validating AIMs is a challenge, as actual climate impacts can not be observed in the present and compared to AIM predictions. We evaluate AIMs by testing their performance on climate analogs in space in the reference climate period. We identify spatial climate analogs in the western US for the 1961-1990 period using 30 year normals of four climate variables (mean maximum temperature of the warmest month, minimum temperature of the coldest month, actual evapotranspiration, and climatic water deficit). We evaluate AIM performance by comparing remotely sensed Landsat tree-canopy data at each pixel of interest (i.e. the observed value) to the tree cover at its candidate analog pixels (i.e. the predicted value) at increasing climatic dissimilarity levels. We find that the AIM predicts tree cover well: the slope of the linear fit of predicted vs actual cover is 0.78 (R2 = 0.78) for climatically closest analogs. Model bias increases and precision decreases with increasing climate dissimilarity between the focal and the analog pixels. Tree cover is often overpredicted for pixels with low tree cover, suggesting that recent disturbance may drive the error at the low cover end. Our study provides support for the utility of climate analogs as a climate impact assessment tool and provides details on the effects of climatic dissimilarity, the number of climate analogs considered, and spatial distribution of spatial analogs on the quality of prediction

Fire Activity and Severity in the Western US Vary along Proxy Gradients Representing Fuel Amount and Fuel Moisture

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios

Understanding Relationships Among Abundance, Extirpation, and Climate at Ecoregional Scales

Recent research on mountain-dwelling species has illustrated changes in species\u27 distributional patterns in response to climate change. Abundance of a species will likely provide an earlier warning indicator of change than will occupancy, yet relationships between abundance and climatic factors have received less attention. We tested whether predictors of counts of American pikas (Ochotona princeps) during surveys from the Great Basin region in 1994-1999 and 2003-2008 differed between the two periods. Additionally, we tested whether various modeled aspects of ecohydrology better predicted relative density than did average annual precipitation, and whether risk of site-wide extirpation predicted subsequent population counts of pikas. We observed several patterns of change in pika abundance at range edges that likely constitute early warnings of distributional shifts. Predictors of pika abundance differed strongly between the survey periods, as did pika extirpation patterns previously reported from this region. Additionally, maximum snowpack and growing-season precipitation resulted in better-supported models than those using average annual precipitation, and constituted two of the top three predictors of pika density in the 2000s surveys (affecting pikas perhaps via vegetation). Unexpectedly, we found that extirpation risk positively predicted subsequent population size. Our results emphasize the need to clarify mechanisms underlying biotic responses to recent climate change at organism-relevant scales, to inform management and conservation strategies for species of concern

Wildland fire deficit and surplus in the western United States, 1984–2012

Wildland fire is an important disturbance agent in the western US and globally. However, the natural role of fire has been disrupted in many regions due to the influence of human activities, which have the potential to either exclude or promote fire, resulting in a ‘‘fire deficit’’ or ‘‘fire surplus’’, respectively. In this study, we developed a model of expected area burned for the western US as a function of climate from 1984 to 2012.We then quantified departures from expected area burned to identify geographic regions with fire deficit or surplus. We developed our model of area burned as a function of several climatic variables from reference areas with low human influence; the relationship between climate and fire is strong in these areas. We then quantified the degree of fire deficit or surplus for all areas of the western US as the difference between expected (as predicted with the model) and observed area burned from 1984 to 2012. Results indicate that many forested areas in the western US experienced a fire deficit from 1984 to 2012, likely due to fire exclusion by human activities. We also found that large expanses of non-forested regions experienced a fire surplus, presumably due to introduced annual grasses and the prevalence of anthropogenic ignitions. The heterogeneity in patterns of fire deficit and surplus among ecoregions emphasizes fundamentally different ecosystem sensitivities to human influences and suggests that largescale adaptation and mitigation strategies will be necessary in order to restore and maintain resilient, healthy, and naturally functioning ecosystems

Wildland fire deficit and surplus in the western United States, 1984–2012

Wildland fire is an important disturbance agent in the western US and globally. However, the natural role of fire has been disrupted in many regions due to the influence of human activities, which have the potential to either exclude or promote fire, resulting in a ‘‘fire deficit’’ or ‘‘fire surplus’’, respectively. In this study, we developed a model of expected area burned for the western US as a function of climate from 1984 to 2012.We then quantified departures from expected area burned to identify geographic regions with fire deficit or surplus. We developed our model of area burned as a function of several climatic variables from reference areas with low human influence; the relationship between climate and fire is strong in these areas. We then quantified the degree of fire deficit or surplus for all areas of the western US as the difference between expected (as predicted with the model) and observed area burned from 1984 to 2012. Results indicate that many forested areas in the western US experienced a fire deficit from 1984 to 2012, likely due to fire exclusion by human activities. We also found that large expanses of non-forested regions experienced a fire surplus, presumably due to introduced annual grasses and the prevalence of anthropogenic ignitions. The heterogeneity in patterns of fire deficit and surplus among ecoregions emphasizes fundamentally different ecosystem sensitivities to human influences and suggests that largescale adaptation and mitigation strategies will be necessary in order to restore and maintain resilient, healthy, and naturally functioning ecosystems

Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data

Environmental limiting factors (ELFs) are the thresholds that determine the maximum or minimum biological response for a given suite of environmental conditions. We asked the following questions: 1) Can we detect ELFs on percent tree cover across the eastern slopes of the Lake Tahoe Basin, NV? 2) How are the ELFs distributed spatially? 3) To what extent are unmeasured environmental factors limiting tree cover? ELFs are difficult to quantify as they require significant sample sizes. We addressed this by using geospatial data over a relatively large spatial extent, where the wall-to-wall sampling ensures the inclusion of rare data points which define the minimum or maximum response to environmental factors. We tested mean temperature, minimum temperature, potential evapotranspiration (PET) and PET minus precipitation (PET-P) as potential limiting factors on percent tree cover. We found that the study area showed system-wide limitations on tree cover, and each of the factors showed evidence of being limiting on tree cover. However, only 1.2% of the total area appeared to be limited by the four (4) environmental factors, suggesting other unmeasured factors are limiting much of the tree cover in the study area. Where sites were near their theoretical maximum, non-forest sites (tree cover \u3c 25%) were primarily limited by cold mean temperatures, open-canopy forest sites (tree cover between 25% and 60%) were primarily limited by evaporative demand, and closed-canopy forests were not limited by any particular environmental factor. The detection of ELFs is necessary in order to fully understand the width of limitations that species experience within their geographic range