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At least 685 records · Page 38Linked to original sources

Social sensing a volcanic eruption: Application to Kīlauea, 2018

Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology, conducted primarily by volcano monitoring and emergency management organisations, but it is complicated by scarce knowledge of how communities respond in times of crisis. Social sensing is a rapidly developing practice that can be adapted for volcanology. Here we use social sensing of Twitter (currently known as X) posts to track changes in social action and reaction throughout the 2018 eruption of Kīlauea on the island of Hawai`i. The volume of relevant posts very rapidly increases in early May, coincident with the beginning of the eruption; automated sentiment analysis shows a simultaneous shift towards more negative emotions being expressed in post text. Substantial negative trends in sentiment are evident in reaction to high-impact events, including the destruction of a popular residential area and injuries sustained by tourists viewing the eruption. Topics of local Twitter conversation reveal societal actions, including the sharing of hazard warnings, mitigation actions, and aid announcements. Temporal trends in societal actions reflect patterns in volcanic activity (e.g. the peak and waning of eruptive activity), civil protection actions (e.g. risk mitigation actions and the communication of official warnings), and socioeconomic pressures (e.g. the destruction of homes). Local tweets detailing eruption damage and disruption display a similar temporal trend to independent estimates of the number of buildings in contact with lava. We show how hazard and risk information is discussed and reacted to on Twitter, which helps inform our understanding of community response actions and aids situational awareness, and outline how our approach could be adapted for use in real time.

Hawaii↗

A climate trend analysis of Sudan

Summer rains in western and southern Sudan have declined by 10-20 percent since the mid-1970s. Observed warming of more than 1 degree Celsius is equivalent to another 10-20 percent reduction in rainfall for crops. The warming and drying have impacted southern Darfur and areas around Juba. Rainfall declines west of Juba threaten southern Sudan's future food production prospects. In many cases, areas with changing climate are coincident with zones of substantial conflict, suggesting some degree of association; however, the contribution of climate change to these conflicts is not currently understood. Rapid population growth and the expansion of farming and pastoralism under a more variable climate regime could dramatically increase the number of at-risk people in Sudan over the next 20 years.

Fact Sheet↗

Site-specific estimation of peak-streamflow frequency using generalized least-squares regression for natural basins in Texas

The U.S. Geological Survey, in cooperation with the Texas Department of Transportation, has developed a computer program to estimate peak-streamflow frequency for ungaged sites in natural basins in Texas. Peak-streamflow frequency refers to the peak streamflows for recurrence intervals of 2, 5, 10, 25, 50, and 100 years. Peak-streamflow frequency estimates are needed by planners, managers, and design engineers for flood-plain management; for objective assessment of flood risk; for cost-effective design of roads and bridges; and also for the desin of culverts, dams, levees, and other flood-control structures. The program estimates peak-streamflow frequency using a site-specific approach and a multivariate generalized least-squares linear regression. A site-specific approach differs from a traditional regional regression approach by developing unique equations to estimate peak-streamflow frequency specifically for the ungaged site. The stations included in the regression are selected using an informal cluster analysis that compares the basin characteristics of the ungaged site to the basin characteristics of all the stations in the data base. The program provides several choices for selecting the stations. Selecting the stations using cluster analysis ensures that the stations included in the regression will have the most pertinent information about flooding characteristics of the ungaged site and therefore provide the basis for potentially improved peak-streamflow frequency estimation. An evaluation of the site-specific approach in estimating peak-streamflow frequency for gaged sites indicates that the site-specific approach is at least as accurate as a traditional regional regression approach.

Texas↗

Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science strategy

The U.S. Geological Survey (USGS) conducts a wide variety of science that improves understanding of droughts and their effects on ecosystems and society. This work includes data collection and monitoring of aquatic and terrestrial systems; assessment and analysis of patterns, trends, drivers, and impacts of drought; development and application of predictive models; and delivery of information and decision-making tools to stakeholders. Stakeholders, which include Federal, Tribal, State, and local agencies, nongovernmental organizations, and others, use this information to anticipate, assess, react to, and mitigate drought conditions and impacts. There is no obvious near-term solution to reduce the frequency and severity of droughts or to mitigate drought impacts. Multidecadal drought is a “grand challenge” that benefits from integration of existing technolo­gies, data, knowledge, and models across related and dispa­rate disciplines, facilitated by new science and technology. In response, the USGS initiated a new integrated-science approach in the Colorado River Basin in 2020. The Colorado River Basin was specifically selected because of concerns about future drought and its consequences for the region. This document explains how the Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) project extends and enhances the science supported by USGS Mission Areas and Programs and articulates scientific gaps and stakeholder needs to identify and reduce drought risks. The approach seeks to answer complex Earth science questions developed in partner­ship with stakeholders about severe long-term drought. An inte­grated approach is required to tackle these complex questions, which any single science discipline cannot answer on its own. In addition to increased understanding of drought and drought effects in complex systems, the Colorado River Basin ASIST project was designed to improve efficiencies through rapid location of a broad array of data sources, assembly of model-ready multidisciplinary data, and delivery of actionable science to stakeholders at the speeds and scales needed for deci­sion making. The project team identified the following actions needed for USGS to implement and advance an integrated science approach in the Colorado River Basin: (1) engage with stakeholders to document their needs and iteratively co-produce science and science delivery tools to address these needs, (2) integrate monitoring and observation systems developed by USGS and other agencies that track droughts and their effects, (3) collect and provide analysis-ready data to support integrated applications, (4) integrate data and model connections to predict multiple drought impacts, (5) conduct multidisciplinary coor­dination to improve interpretations, (6) leverage the knowledge base across USGS to enhance decision making, and (7) support the development of new integrated science approaches and technologies that provide analysis and management tools that can be used to adapt to the effects of drought in the Colorado River Basin. Proposals for initial short-term use-case projects were solicited, a subset of which was selected for funding to test implementation of these actions. Additionally, the project organized and convened a series of science and technology collaboration workshops in the USGS focused on challenges that were identified and prioritized by the short-term use-case projects and during the initial stakeholder analysis. These work­shops were designed to bring together diverse perspectives to discuss science and technology challenges, stakeholder needs, capabilities, and knowledge gaps, with the goal of determin­ing how the USGS can address challenges, identify future opportunities for continued engagement between participants, and inform the next steps for the Colorado River Basin ASIST project. Continuing to collaboratively engage with a wide range of stakeholders using an integrated approach will provide a suitable foundation of data and tools to formulate actionable intelligence for predicting droughts and informing adaptation to the effects of long-term drought in a holistic, timely, and effective manner.

Arizona, California, Colorado, Nevada, New Mexico,↗

Cougar survival and source-sink structure on Greater Yellowstone's Northern Range

We studied survival and causes of mortality of radiocollared cougars ( Puma concolor ) on the Greater Yellowstone Northern Range (GYNR) prior to (1987–1994) and after wolf ( Canis lupus ) reintroduction (1998–2005) and evaluated temporal, spatial, and environmental factors that explain variation in adult, subadult, and kitten survival. Using Program MARK and multimodel inference, we modeled cougar survival based on demographic status, season, and landscape attributes. Our best models for adult and independent subadults indicated that females survived better than males and survival increased with age until cougars reached older ages. Lower elevations and increasing density of roads, particularly in areas open to cougar hunting north of Yellowstone National Park (YNP), increased mortality risks for cougars on the GYNR. Indices of ungulate biomass, cougar and wolf population size, winter severity, rainfall, and individual characteristics such as the presence of dependent young, age class, and use of Park or Wilderness were not important predictors of survival. Kitten survival increased with age, was lower during winter, increased with increasing minimum estimates of elk calf biomass, and increased with increasing density of adult male cougars. Using our best model, we mapped adult cougar survival on the GYNR landscape. Results of receiver operating characteristic (ROC) analysis indicated a good model fit for both female (area under the curve [AUC] = 0.81, 95%CI = 0.70–0.92, n  = 35 locations) and male cougars (AUC = 0.84, 95%CI = 0.74–0.94, n  = 49 locations) relative to hunter harvest locations in our study area. Using minimum estimates of survival necessary to sustain the study population, we developed a source-sink surface and we identify several measures that resource management agencies can take to enhance cougar population management based on a source-sink strategy.

Montana, Wyoming↗

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log 10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.

Texas↗

Movement analysis of free-grazing domestic ducks in Poyang Lake, China: A disease connection

Previous work suggests domestic poultry are important contributors to the emergence and transmission of highly pathogenic avian influenza throughout Asia. In Poyang Lake, China, domestic duck production cycles are synchronized with arrival and departure of thousands of migratory wild birds in the area. During these periods, high densities of juvenile domestic ducks are in close proximity to migratory wild ducks, increasing the potential for the virus to be transmitted and subsequently disseminated via migration. In this paper, we use GPS dataloggers and dynamic Brownian bridge models to describe movements and habitat use of free-grazing domestic ducks in the Poyang Lake basin and identify specific areas that may have the highest risk of H5N1 transmission between domestic and wild birds. Specifically, we determine relative use by free-grazing domestic ducks of natural wetlands, which are the most heavily used areas by migratory wild ducks, and of rice paddies, which provide habitat for resident wild ducks and lower densities of migratory wild ducks. To our knowledge, this is the first movement study on domestic ducks, and our data show potential for free-grazing domestic ducks from farms located near natural wetlands to come in contact with wild waterfowl, thereby increasing the risk for disease transmission. This study provides an example of the importance of movement ecology studies in understanding dynamics such as disease transmission on a complicated landscape.

Poyang Lake↗

The underlying causes of differential migration: Assumptions, hypotheses, and predictions

Mechanisms governing the migratory decisions of birds have long fascinated ecologists and sparked considerable debate. Identifying factors responsible for variation in migration distance, also known as differential migration, has been a popular approach to understanding the mechanisms underlying migratory behaviour more generally. However, research progress has been slowed by the continued testing of overlapping, non-mechanistic, and circular predictions among a small set of historically entrenched hypotheses. We highlight the body size hypothesis and suggest that the predictions commonly tested have impeded progress because body size relationships with migration distance are predictions made by several distinct hypotheses with contrasting mechanisms. The cost of migration itself has not been adequately accounted for in most hypotheses, and we propose two flight efficiency hypotheses with time- and energy-minimizing mechanisms that allow individuals to mitigate the risks inherent to longer migrations. We also advance two conceptual versions of the social dominance hypothesis based on two distinct underlying mechanisms related to distance minimization and food maximization that will help clarify the role of competition in driving migratory decisions. Overall, we describe and refine 12 mechanistic hypotheses proposed to explain differential migration (along with several other special-case hypotheses), seven of which have underlying mechanisms related to food limitation as past research has identified this to be an important driver of differential migration. We also thoroughly reviewed 145 publications to assess the amount of support for 10 critical assumptions underlying alternative hypotheses for differential migration in birds. Our review reveals that surprisingly few studies explicitly evaluate assumptions within a differential migration context. Generating and testing strong predictions and critical assumptions underlying mechanisms of alternative hypotheses will improve our ability to differentiate among these explanations of differential migration. Additionally, future intraspecific progress will be greatest if investigators continue to focus on mechanisms underlying variation in migration distance within rather than among demographic classes, as previous research has found differing mechanisms to be responsible for differential migration among demographic classes. Interspecifically, a thorough comparative analysis that seeks to explain variation in migration distance among species would broaden both our understanding of the mechanisms regulating current differential migration patterns and those that led to the evolution of migration more generally. Collectively, we provide a framework that, together with advances in animal-borne tracking and other technology, can be used to advance our understanding of the causes of differential migration distance, and migratory decisions more generally.

Biological Reviews↗

Towards common ground in the biodiversity–disease debate

The disease ecology community has struggled to come to consensus on whether biodiversity reduces or increases infectious disease risk, a question that directly affects policy decisions for biodiversity conservation and public health. Here, we summarize the primary points of contention regarding biodiversity–disease relationships and suggest that vector-borne, generalist wildlife and zoonotic pathogens are the types of parasites most likely to be affected by changes to biodiversity. One synthesis on this topic revealed a positive correlation between biodiversity and human disease burden across countries, but as biodiversity changed over time within these countries, this correlation became weaker and more variable. Another synthesis—a meta-analysis of generally smaller-scale experimental and field studies—revealed a negative correlation between biodiversity and infectious diseases (a dilution effect) in various host taxa. These results raise the question of whether biodiversity–disease relationships are more negative at smaller spatial scales. If so, biodiversity conservation at the appropriate scales might prevent wildlife and zoonotic diseases from increasing in prevalence or becoming problematic (general proactive approaches). Further, protecting natural areas from human incursion should reduce zoonotic disease spillover. By contrast, for some infectious diseases, managing particular species or habitats and targeted biomedical approaches (targeted reactive approaches) might outperform biodiversity conservation as a tool for disease control. Importantly, biodiversity conservation and management need to be considered alongside other disease management options. These suggested guiding principles should provide common ground that can enhance scientific and policy clarity for those interested in simultaneously improving wildlife and human health.

Nature Ecology & Evolution↗

A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data

Conservation planning for rare and threatened species is often made more difficult by a lack of research and monitoring data. In such cases, managers may rely on qualitative assessments of species risk that lack explicit acknowledgement of uncertainty. Snakes are a group of conservation concern that are also notoriously difficult to monitor. Here, we demonstrate a quantitative population projection for a data-deficient species, the Puerto Rican boa ( Chilabothrus inornatus ) using expert knowledge and published information about species life history and threats to persistence. Using this model, we simulated population dynamics over 30 years under four scenarios of future urbanization and found that there was an increased probability of population decline as urbanization rates increased. We conduct a sensitivity analysis to evaluate the sensitivity of outcomes to model inputs, a practice that may also be useful in recovery planning. The sensitivity analyses also provide insight into how the future trajectories would change if the elicited demographic rates are incorrect. Even when data are sparse, quantitative methods can often be used to produce rigorous and reproducible estimates of future status with quantifiable uncertainty.

Puerto Rico↗

Regression equations for estimation of annual peak-streamflow frequency for undeveloped watersheds in Texas using an L-moment-based, PRESS-minimized, residual-adjusted approach

Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed characteristics of drainage area, dimensionless main-channel slope, and mean annual precipitation. The residuals of the nine equations are spatially mapped, and residuals for the 10-year recurrence interval are selected for generalization to 1-degree latitude and longitude quadrangles. The generalized residual is referred to as the OmegaEM parameter and represents a generalized terrain and climate index that expresses peak-streamflow potential not otherwise represented in the three watershed characteristics. The OmegaEM parameter was assigned to each station, and using OmegaEM, nine additional regression equations are computed. Because of favorable diagnostics, the OmegaEM equations are expected to be generally reliable estimators of peak-streamflow frequency for undeveloped and ungaged stream locations in Texas. The mean residual standard error, adjusted R-squared, and percentage reduction of PRESS by use of OmegaEM are 0.30log 10 , 0.86, and -21 percent, respectively. Inclusion of the OmegaEM parameter provides a substantial reduction in the PRESS statistic of the regression equations and removes considerable spatial dependency in regression residuals. Although the OmegaEM parameter requires interpretation on the part of analysts and the potential exists that different analysts could estimate different values for a given watershed, the authors suggest that typical uncertainty in the OmegaEM estimate might be about +or-0.10 10 . Finally, given the two ensembles of equations reported herein and those in previous reports, hydrologic design engineers and other analysts have several different methods, which represent different analytical tracks, to make comparisons of peak-streamflow frequency estimates for ungaged watersheds in the study area.

Texas↗

Research to inform Caltrans best management practices for reptile and amphibian road crossings

In October of 2014, the U.S. Geological Survey (USGS) began a 5-year project to conduct research to inform Best Management Practices (BMPs) for amphibian and reptile crossing and barrier systems in California. To inform future conservation and transportation planning, this project involved identification of species at highest risk of negative road impacts, creation of geodatabase and spatial mapping tools that crosswalk with California Essential Habitat Connectivity Planning, and field research to address information gaps in the efficacy of reptile and amphibian passage and barrier systems. Per the agreement with California Department of Transportation (Caltrans; agreement 65A0553), this project was part of a broader collaborative effort between the Western Transportation Institute (WTI) of Montana State University and USGS Western Ecological Research Center (WERC). As part of this broader project, WTI conducted a worldwide literature review and gap analysis and produced the BMP manual for herpetofauna in California. WTI and USGS were contracted separately although we worked closely together throughout this broader effort and each brought particular expertise to the project. WTI has expertise in highways, the attributes of the highway environment, and has broad international experience with road ecology and herpetofauna connectivity systems worldwide. USGS WERC has expertise with California amphibian and reptile species and their ecology, study design and implementation, as well as expertise in landscape connectivity and road ecology.

California↗

Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA

Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications ( i.e. , road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride ( i.e. , hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.

Delaware, Maryland, New Jersey, New York, Pennsylv↗

Comparing population exposure to multiple Washington earthquake scenarios for prioritizing loss estimation studies

Scenario-based, loss-estimation studies are useful for gauging potential societal impacts from earthquakes but can be challenging to undertake in areas with multiple scenarios and jurisdictions. We present a geospatial approach using various population data for comparing earthquake scenarios and jurisdictions to help emergency managers prioritize where to focus limited resources on data development and loss-estimation studies. Using 20 earthquake scenarios developed for the State of Washington (USA), we demonstrate how a population-exposure analysis across multiple jurisdictions based on Modified Mercalli Intensity (MMI) classes helps emergency managers understand and communicate where potential loss of life may be concentrated and where impacts may be more related to quality of life. Results indicate that certain well-known scenarios may directly impact the greatest number of people, whereas other, potentially lesser-known, scenarios impact fewer people but consequences could be more severe. The use of economic data to profile each jurisdiction’s workforce in earthquake hazard zones also provides additional insight on at-risk populations. This approach can serve as a first step in understanding societal impacts of earthquakes and helping practitioners to efficiently use their limited risk-reduction resources.

Washington↗

Evidence for range contraction of snowshoe hare in Pennsylvania

In Pennsylvania, Lepus americanus (Snowshoe Hare) is near the southern limits of its range and at risk of range contraction because of loss of early-successional forest and impacts of climate change. We used hunter-harvest data to investigate changes in the distribution of Snowshoe Hare in Pennsylvania (1983–2011), forest inventory and land-use data to assess changes in amount and distribution of early-successional forest (1988–2011), and occupancy modeling (2004) to identify habitat and climate variables that explain the current distribution of Snowshoe Hare. We determined presence of Snowshoe Hare based on visual sightings, observations of tracks, and DNA analysis of fecal pellets, and used repeated visits to sampling sites and occupancy models to estimate occupancy rates (Ψ). Hunter-harvest data indicated the range of Snowshoe Hare in Pennsylvania contracted towards northwestern and northeastern portions of the state. Based on occupancy modeling, Snowshoe Hare were most likely to occupy early-successional and mixed deciduous-coniferous forest types and areas with colder winter temperatures, which coincided with the distribution of hunter harvests. Among the 4 forest types, we estimated Ψ = 0.52-0.79 and Ψ = 0.10-0.32 where winter temperatures were coldest and warmest, respectively. Total forest loss was <1% during 1988-2011, and the loss of early-successional forest in the current and former range of Snowshoe Hares was similar as were mean patch size and a fragmentation metric of early-successional habitat. Thus, changes in forest characteristics did not explain the range contraction we observed. We used climate-model predictions and our occupancy model to predict that average occupancy probability across northern Pennsylvania may decline from 0.27 in 2004 to 0.10–0.18 by 2050–2059, depending on the climate model. The range of Snowshoe Hare in Pennsylvania has contracted to regions of Pennsylvania with the coldest winter temperatures and most persistent snowpack, and based on projected climate change, our results suggest further range contraction of Snowshoe Hare in Pennsylvania.

Pennsylvania↗

Geographic distribution of genetic diversity in populations of Rio Grande Chub Gila pandora

In the southwestern United States (US), the Rio Grande chub ( Gila pandora) is state-listed as a fish species of greatest conservation need and federally listed as sensitive due to habitat alterations and competition with non-native fishes. Characterizing genetic diversity, genetic population structure, and effective number of breeders will assist with conservation efforts by providing a baseline of genetic metrics. Genetic relatedness within and among G. pandora populations throughout New Mexico was characterized using 11 microsatellite loci among 15 populations in three drainage basins (Rio Grande, Pecos, Canadian). Observed heterozygosity (H O ) ranged from 0.71&ndash;0.87 and was similar to expected heterozygosity (0.75&ndash;0.87). Rio Ojo Caliente (Rio Grande) had the highest allelic richness (A R = 15.09), while Upper Rio Bonito (Pecos) had the lowest allelic richness (A R = 6.75). Genetic differentiation existed among all populations with the lowest genetic variation occurring within the Pecos drainage. STRUCTURE analysis revealed seven genetic clusters. Populations of G. pandora within the upper Rio Grande drainage (Rio Ojo Caliente, Rio Vallecitos, Rio Pueblo de Taos) had high levels of admixture with Q-values ranging from 0.30&ndash;0.50. In contrast, populations within the Pecos drainage (Pecos River and Upper Rio Bonito) had low levels of admixture (Q = 0.94 and 0.87, respectively). Estimates of effective number of breeders ( N b ) varied from 6.1 (Pecos: Upper Rio Bonito) to 109.7 (Rio Grande: Rio Pe&ntilde;asco) indicating that populations in the Pecos drainage are at risk of extirpation. In the event that management actions are deemed necessary to preserve or increase genetic diversity of G. pandora , consideration must be given as to which populations are selected for translocation.

Arizona, California, Colorado, Nevada, New Mexico,↗

Quasi-periodic recurrence of large earthquakes on the southern San Andreas fault

It has been 153 yr since the last large earthquake on the southern San Andreas fault (California, United States), but the average interseismic interval is only ~100 yr. If the recurrence of large earthquakes is periodic, rather than random or clustered, the length of this period is notable and would generally increase the risk estimated in probabilistic seismic hazard analyses. Unfortunately, robust characterization of a distribution describing earthquake recurrence on a single fault is limited by the brevity of most earthquake records. Here we use statistical tests on a 3000 yr combined record of 29 ground-rupturing earthquakes from Wrightwood, California. We show that earthquake recurrence there is more regular than expected from a Poisson distribution and is not clustered, leading us to conclude that recurrence is quasi-periodic. The observation of unimodal time dependence is persistent across an observationally based sensitivity analysis that critically examines alternative interpretations of the geologic record. The results support formal forecast efforts that use renewal models to estimate probabilities of future earthquakes on the southern San Andreas fault. Only four intervals (15%) from the record are longer than the present open interval, highlighting the current hazard posed by this fault.

California↗

Regional skew for California, and flood frequency for selected sites in the Sacramento-San Joaquin River Basin, based on data through water year 2006

Improved flood-frequency information is important throughout California in general and in the Sacramento-San Joaquin River Basin in particular, because of an extensive network of flood-control levees and the risk of catastrophic flooding. A key first step in updating flood-frequency information is determining regional skew. A Bayesian generalized least squares (GLS) regression method was used to derive a regional-skew model based on annual peak-discharge data for 158 long-term (30 or more years of record) stations throughout most of California. The desert areas in southeastern California had too few long-term stations to reliably determine regional skew for that hydrologically distinct region; therefore, the desert areas were excluded from the regional skew analysis for California. Of the 158 long-term stations used to determine regional skew, 145 have minimally regulated annual-peak discharges, and 13 stations are dam sites for which unregulated peak discharges were estimated from unregulated daily maximum discharge data furnished by the U.S. Army Corp of Engineers. Station skew was determined by using an expected moments algorithm (EMA) program for fitting the Pearson Type 3 flood-frequency distribution to the logarithms of annual peak-discharge data. The Bayesian GLS regression method previously developed was modified because of the large cross correlations among concurrent recorded peak discharges in California and the use of censored data and historical flood information with the new expected moments algorithm. In particular, to properly account for these cross-correlation problems and develop a suitable regression model and regression diagnostics, a combination of Bayesian weighted least squares and generalized least squares regression was adopted. This new methodology identified a nonlinear function relating regional skew to mean basin elevation. The regional skew values ranged from -0.62 for a mean basin elevation of zero to 0.61 for a mean basin elevation of 11,000 feet. This relation between skew and elevation reflects the interaction of snow with rain, which increases with increased elevation. The equivalent record length for the new regional skew ranges from 52 to 65 years of record, depending upon mean basin elevation. The old regional skew map in Bulletin 17B, published by the Hydrology Subcommittee of the Interagency Advisory Committee on Water Data (1982), reported an equivalent record length of only 17 years. The newly developed regional skew relation for California was used to update flood frequency for the 158 sites used in the regional skew analysis as well as 206 selected sites in the Sacramento-San Joaquin River Basin. For these sites, annual-peak discharges having recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years were determined on the basis of data through water year 2006. The expected moments algorithm was used for determining the magnitude and frequency of floods at gaged sites by using regional skew values and using the basic approach outlined in Bulletin

Scientific Investigations Report↗