Climatic Metrics Research Articles

Testing alternative models of climate‐mediated extirpations

Biotic responses to climate change will vary among taxa and across latitudes, elevational gradients, and degrees of insularity. However, due to factors such as phenotypic plasticity, ecotypic variation, and evolved tolerance to thermal stress, it remains poorly understood whether losses should be greatest in populations experiencing the greatest climatic change or living in places where the prevailing climate is closest to the edge of the species' bioclimatic envelope (e.g., at the hottest, driest sites). Research on American pikas (Ochotona princeps) in montane areas of the Great Basin during 1994-1999 suggested that 20th-century population extirpations were predicted by a combination of biogeographic, anthropogenic, and especially climatic factors. Surveys during 2005-2007 documented additional extirpations and within-site shifts of pika distributions at remaining sites. To evaluate the evidence in support of alternative hypotheses involving effects of thermal stress on pikas, we placed temperature sensors at 156 locations within pika habitats in the vicinity of 25 sites with historical records of pikas in the Basin. We related these time series of sensor data to data on ambient temperature from weather stations within the Historical Climate Network. We then used these highly correlated relationships, combined with long-term data from the same weather stations, to hindcast temperatures within pika habitats from 1945 through 2006. To explain patterns of loss, we posited three alternative classes of direct thermal stress: (1) acute cold stress (number of days below a threshold temperature); (2) acute heat stress (number of days above a threshold temperature); and (3) chronic heat stress (average summer temperature). Climate change was defined as change in our thermal metrics between two 31-yr periods: 1945-1975 and 1976-2006. We found that patterns of persistence were well predicted by metrics of climate. Our best models suggest some effects of climate change; however, recent and long-term metrics of chronic heat stress and acute cold stress, neither previously recognized as sources of stress for pikas, were some of the best predictors of pika persistence. Results illustrate that extremely rapid distributional shifts can be explained by climatic influences and have implications for conservation topics such as reintroductions and early-warning indicators.

Catchment transit times and landscape controls—does scale matter?

AbstractMean transit times (MTTs) can give useful insights into the internal processes of hydrological systems. However, our understanding of how they vary and scale remains unclear. We used MTT estimates obtained from δ18O data from 20, mostly nested, contrasting catchments in North East Scotland, ranging from 1 to 1700 km2. The estimated MTTs ranged between 270 and 1170 days and were used to test a previously developed multiple linear regression (MLR) model for MTT prediction based on metrics of soil cover, landscape organization and climate. We show that the controls on MTT identified by the MLR model hold with the independent data from these 20 sites and that the MLR can be used to predict MTT in ungauged montane catchments. The dominant controls also remain unchanged over four orders of magnitude of catchment size, suggesting no major change of dominant flow paths and mixing processes at larger scales. This is consistent with the fact that only the variance of MTT, rather than MTT, showed a scaling relationship. MTTs appeared to converge with increasing catchment scale, apparently due to the integration of heterogeneous headwater responses in larger downstream catchments. Copyright © 2009 John Wiley & Sons, Ltd.

How spatially coherent and statistically robust are temporal changes in extreme precipitation in the contiguous USA?

AbstractCentury‐long precipitation records from stations in the contiguous USA indicate an increased frequency of rainy days over the past century and some evolution in the probability distributions of precipitation amount. Temporal trends in eight metrics of the precipitation climate are of similar magnitude and sign regardless of whether they are derived from bootstrapping of regression residuals or using the Kendall's tau statistic, though the bootstrap technique generally resolved a larger number of ‘significant’ trends. There is substantial variability in terms of the magnitude, significance and sign of the linear trends with specific metrics, and they are sensitive to recording bias of light precipitation events in the early part of the 20th century. The majority of stations that exhibit significant linear trends show evidence of increases in the intensity of events above the 95th percentile. The resolved trends tend to have a larger magnitude at the end of the century. Spatial variability as manifest in the spatial autocorrelation in the interannual variability and trends in extreme metrics is manifest at a range of scales, but in general the correlation between stations is significant only for separation of distances of a few tens of kilometres. The largest trends towards increased annual total precipitation, number of rainy days and intense precipitation (e.g. fraction of precipitation derived from events in excess of the 90th percentile value) are focussed on the Central Plains/northwestern Midwest. Copyright © 2008 Royal Meteorological Society

Organizational Climate Metrics as Safety, Health and Environment Performance Indicators and an Aid to Relative Risk Ranking within Industry

The chemical, pharmaceutical and other related process industries are characterized by inherently hazardous processes and activities. To ensure that considered risk management decisions are made it is essential that organizations have the ability to rank the risk profiles of their assets and operations. Current industry risk ranking techniques are biased toward the assessment of the risk potential of the asset or operation. Methodologies used to assess these risks tend to be engineering-based and include, for example, hazard identification and event rate estimation techniques. Recent research has associated lagging safety performance indicators with metrics of organizational safety climate. Despite the evidence suggesting their potential usefulness, organizational climate metrics have not yet been exploited as a proactive safety, health and environmental performance indicator or as an aid to relative risk ranking. This paper summarizes research that successfully produced a statistical model of organizational climate and its relationship to site significant injury frequency rates, allowing the relative risk ranking of sites based upon organizational climate metrics. The responses to an industrial organizational survey are examined for a pharmaceutical company's sites in the United Kingdom, Sweden and the United States. Projection to Latent Structures Analysis is performed on the survey responses. The resultant models are shown to be able to accurately model the site significant injury frequency rates. The organizational climate metrics that discriminate between the safety performance levels of different sites are identified.