A general-purpose parallel raster processing programming library test application using a geographic cellular automata model

A general-purpose parallel raster processing programming library (pRPL) was developed and applied to speed up a commonly used cellular automaton model with known tractability limitations. The library is suitable for use by geographic information scientists with basic programming skills, but who lack knowledge and experience of parallel computing and programming. pRPL is a general-purpose programming library that provides generic support for raster processing, including local-scope, neighborhood-scope, regional-scope, and global-scope algorithms as long as they are parallelizable. The library also supports multilayer algorithms. Besides the standard data domain decomposition methods, pRPL provides a spatially adaptive quad-tree-based decomposition to produce more evenly distributed workloads among processors. Data parallelism and task parallelism are supported, with both static and dynamic load-balancing. By grouping processors, pRPL also supports data–task hybrid parallelism, i.e., data parallelism within a processor group and task parallelism among processor groups. pSLEUTH, a parallel version of a well-known cellular automata model for simulating urban land-use change (SLEUTH), was developed to demonstrate full utilization of the advanced features of pRPL. Experiments with real-world data sets were conducted and the performance of pSLEUTH measured. We conclude not only that pRPL greatly reduces the development complexity of implementing a parallel raster-processing algorithm, it also greatly reduces the computing time of computationally intensive raster-processing algorithms, as demonstrated with pSLEUTH.     

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.     

A bundle adjustment approach with inner constraints for the scaled orthographic projection

Bundle adjustment is a method for simultaneously calculating both the interior and exterior orientation parameters of a set of images, and the object-space coordinates of the observed points. In the case of long focal length lenses and narrow field-of-view (FOV) imaging situations, collinearity based (perspective projection) algorithms may result in linear dependencies between parameters that cause solution instability. The use of a scaled orthographic projection model based on linear algebraic formulations was therefore adopted to reduce this risk. Using quaternions, a new mathematical model is derived that includes the partial derivatives as well as the inner constraint equations for a scaled orthographic bundle adjustment. The model was then tested using two image sets of a single, small vessel (about 6 m length) with a cube target of known dimensions at two distinct ranges; perspective solutions were also calculated for comparison. RMS residual errors of 0.74-0.78 pixels associated with the new method compare favorably to a residual error range of 0.59-0.74 pixels using a perspective bundle adjustment of the same target points. Relative precisions (as a ratio of target size) of between 1:1650 and 1:750 have been achieved at ranges of 375 m and 850 m, respectively, given comparisons with the known cube dimensions. A third image dataset consisting of a network of 16 images was solved with a 1:2200 relative precision showing the new method can successfully handle high redundancy. For the experiments that were conducted, the new method was found to produce less precise results than the perspective bundle solution for a FOV of 0.50-0.65° where the object fills 5-8% of the image. However, it was found to match the precision of the perspective model (with an uncalibrated camera) for a FOV of 0.20-0.30° where the object of interest fills only 1-2% of the full image.     

Hurricane effects on subtropical pine rocklands of the Florida Keys

We investigate the effects of Hurricane Wilma??s storm surge (23?C24 October 2005) on the dominant tree Pinus elliottii var densa (South Florida slash pine) and rare plant species in subtropical pine rocklands of the Lower Florida Keys. We examine the role of elevation on species abundance in 1995 (Hurricane Betsy in 1965), 2005 (Hurricane Georges in 1998), and 2008 (Hurricane Wilma in 2005) to investigate if hurricanes influence abundance by eliminating plants at lower elevation on Big Pine Key, the largest island in the Lower Florida Keys. We compare densities before and after Hurricane Wilma over the 2005?C2008 sampling period and examine the role of elevation on changes in pine and rare species densities three years after Hurricane Wilma. We use elevation to assess the impact of hurricanes because elevation determined whether a location was influenced by storm surge (maximum surge of 2 m) in the Lower Florida Keys, where pine rocklands occur at a maximum elevation of 3 m. In 1995 (30 years after a major storm), elevation did not explain the abundance of South Florida slash pine or Chamaecrista lineata, but explained significant variation in abundance of Chamaesyce deltoidea. The latter two species are rare herbaceous plants restricted to pine rocklands. In 2008, 3 years after Hurricane Wilma, the positive relationship between elevation and abundance was strongest for South Florida slash pine, C. deltoidea, and C. lineata. Effects of Hurricane Wilma were not significant for rare species with wider distribution, occurring in plant communities adjacent to pine rocklands and in disturbed rocklands. Our results suggest that hurricanes drive population dynamics of South Florida slash pine and rare species that occur exclusively in pine rocklands at higher elevations. Rare species restricted to pine rocklands showed dramatic declines after Hurricane Wilma and were eliminated at elevations <0.5 m. Widely distributed rare species did not show significant changes in density after Hurricane Wilma. Abundance increased with elevation for South Florida slash pine and C. lineata after the hurricane. In an environment influenced by sea level rise, concrete plans to conserve pine ecosystems are warranted. Results from this study will help define conservation strategies by strengthening predictive understanding of plant responses to disturbance in the backdrop of sea level rise.     

The potential to narrow uncertainty in projections of regional precipitation change

We separate and quantify the sources of uncertainty in projections of regional (～2,500 km) precipitation changes for the twenty-first century using the CMIP3 multi-model ensemble, allowing a direct comparison with a similar analysis for regional temperature changes. For decadal means of seasonal mean precipitation, internal variability is the dominant uncertainty for predictions of the first decade everywhere, and for many regions until the third decade ahead. Model uncertainty is generally the dominant source of uncertainty for longer lead times. Scenario uncertainty is found to be small or negligible for all regions and lead times, apart from close to the poles at the end of the century. For the global mean, model uncertainty dominates at all lead times. The signal-to-noise ratio (S/N) of the precipitation projections is highest at the poles but less than 1 almost everywhere else, and is far lower than for temperature projections. In particular, the tropics have the highest S/N for temperature, but the lowest for precipitation. We also estimate a ‘potential S/N’ by assuming that model uncertainty could be reduced to zero, and show that, for regional precipitation, the gains in S/N are fairly modest, especially for predictions of the next few decades. This finding suggests that adaptation decisions will need to be made in the context of high uncertainty concerning regional changes in precipitation. The potential to narrow uncertainty in regional temperature projections is far greater. These conclusions on S/N are for the current generation of models; the real signal may be larger or smaller than the CMIP3 multi-model mean. Also note that the S/N for extreme precipitation, which is more relevant for many climate impacts, may be larger than for the seasonal mean precipitation considered here.     

Changes of interannual NAO variability in response to greenhouse gases forcing

Observations show that there was change in interannual North Atlantic Oscillation (NAO) variability in the mid-1970s. This change was characterized by an eastward shift of the NAO action centres, a poleward shift of zonal wind anomalies and a downstream extension of climate anomalies associated with the NAO. The NAO interannual variability for the period after the mid-1970s has an annular mode structure that penetrates deeply into the stratosphere, indicating a strengthened relationship between the NAO and the Arctic Oscillation (AO) and strengthened stratosphere-troposphere coupling. In this study we have investigated possible causes of these changes in the NAO by carrying out experiments with an atmospheric GCM. The model is forced either by doubling CO₂, or increasing sea surface temperatures (SST), or both. In the case of SST forcing the SST anomaly is derived from a coupled model simulation forced by increasing CO₂. Results indicate that SST and CO₂ change both force a poleward and eastward shift in the pattern of interannual NAO variability and the associated poleward shift of zonal wind anomalies, similar to the observations. The effect of SST change can be understood in terms of mean changes in the troposphere. The direct effect of CO₂ change, in contrast, can not be understood in terms of mean changes in the troposphere. However, there is a significant response in the stratosphere, characterized by a strengthened climatological polar vortex with strongly enhanced interannual variability. In this case, the NAO interannual variability has a strong link with the variability over the North Pacific, as in the annular AO pattern, and is also strongly related to the stratospheric vortex, indicating strengthened stratosphere-troposphere coupling. The similarity of changes in many characteristics of NAO interannual variability between the model response to doubling CO₂ and those in observations in the mid-1970s implies that the increase of greenhouse gas concentration in the atmosphere, and the resulting changes in the stratosphere, might have played an important role in the multidecadal change of interannual NAO variability and its associated climate anomalies during the late twentieth century. The weak change in mean westerlies in the troposphere in response to CO₂ change implies that enhanced and eastward extended mid-latitude westerlies in the troposphere might not be a necessary condition for the poleward and eastward shift of the NAO action centres in the mid-1970s.     

Cytochrome P4501A biomarker indication of the timeline of chronic exposure of Barrow's goldeneyes to residual Exxon Valdez oil

We examined hepatic EROD activity, as an indicator of CYP1A induction, in Barrow’s goldeneyes captured in areas oiled during the 1989 Exxon Valdez spill and those from nearby unoiled areas. We found that average EROD activity differed between areas during 2005, although the magnitude of the difference was reduced relative to a previous study from 1996/1997, and we found that areas did not differ by 2009. Similarly, we found that the proportion of individuals captured from oiled areas with elevated EROD activity (?2 times unoiled average) declined from 41% in winter 1996/1997 to 10% in 2005 and 15% in 2009. This work adds to a body of literature describing the timelines over which vertebrates were exposed to residual Exxon Valdez oil and indicates that, for Barrow’s goldeneyes in Prince William Sound, exposure persisted for many years with evidence of substantially reduced exposure by 2 decades after the spill.     

Contrasting isotopic signatures between anthropogenic and geogenic Zn and evidence for post-depositional fractionation processes in smelter-impacted soils from Northern France

Zinc isotopes have been studied along two smelter-impacted soil profiles sampled near one of the largest Pb and Zn processing plants in Europe located in northern France, about 50 km south of Lille. Mean δ⁶⁶Zn values along these two soil profiles range from +0.22 ± 0.17‰ (2σ) to +0.34 ± 0.17‰ (2σ) at the lowest horizons and from +0.38 ± 0.45‰ (2σ) to +0.76 ± 0.14‰ (2σ) near the surface. The δ⁶⁶Zn values in the lowest horizons of the soils are interpreted as being representative of the local geochemical background (mean value +0.31 ± 0.38‰), whereas heavier δ⁶⁶Zn values near the surface of the two soils are related to anthropogenic Zn. This anthropogenic Zn occurs in the form of franklinite (ZnFe₂O₄)-bearing slag grains originating from processing wastes at the smelter site and exhibiting δ⁶⁶Zn values of +0.81 ± 0.20‰ (2σ). The presence of franklinite is indicated by EXAFS analysis of the topsoil samples from both soil profiles as well as by micro-XANES analysis of the surface horizon of a third smelter-impacted soil from a distant site. These results indicate that naturally occurring Zn and smelter-derived Zn exhibit significantly different δ⁶⁶Zn values, which suggests that zinc isotopes can be used to distinguish between geogenic and anthropogenic sources of Zn in smelter-impacted soils. In addition to a possible influence of additional past sources of light Zn (likely Zn-sulfides and Zn-sulfates directly emitted by the smelter), the light δ⁶⁶Zn values in the surface horizons compared to smelter-derived slag materials are interpreted as resulting mainly from fractionation processes associated with biotic and/or abiotic pedological processes (Zn-bearing mineral precipitation, Zn complexation by organic matter, and plant uptake of Zn). This conclusion emphasizes the need for additional Zn isotopic studies before being able to use Zn isotopes to trace sources and pathways of this element in surface environments.     

On the use of IPCC-class models to assess the impact of climate on Living Marine Resources

The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.