Large Geographic Regions Research Articles

Copula-based reliability modelling of wireless sensor networks with dependent failures

Wireless sensor networks (WSNs) have widely been applied in various industries and business fields covering large geographical regions. It is therefore important to be able to model, assess and predict the reliability of WSNs since the failures can have a great effect on the monitoring or control systems that are normally depending on the WSNs. In this paper, the general WSN reliability models are developed by deleting the independent assumption of component or subsystem failures and are consequently more reasonable to characterise the failure process of WSNs. The methodology in the proposed WSN reliability models is to consider that the failure times of subsystems are dependent variables and their joint distribution is obtained by binding their marginal failure distributions together through a copula function. For specific Frank copula functions, the Star-based WSN reliability models are derived and their properties are also discussed in this paper.

Two additions to the moss flora of the South Shetland Islands in the maritime Antarctic

<em>Tortella fragilis</em> (Drumm.) Limpr. (Pottiaceae) and <em>Bryum nivale</em> Müll. Hal. (Bryaceae) are recorded for the first time from the South Shetland Islands in the northern maritime Antarctic. They were discovered in the Admiralty Bay area on King George Island, the largest island of this archipelago. The two species are briefly characterized morphologically, their habitats are described, and their distribution in the Antarctic is mapped. Discovery of these species has increased the documented moss flora of King George Island to 67 species, strengthening it in the leading position among individual areas with the richest diversity of moss flora in Antarctica. Likewise, <em>T. fragilis</em> and <em>B. nivale</em> represent remarkable additions to the moss flora of the South Shetland Islands, which currently consists of 92 species and one variety, making this archipelago by far the richest bryofloristically amongst large geographic regions of the Antarctic. Comparison of recent (2018) and old (1985) photographs revealed a significant retreat of glacial cover and suggests that the collection site was likely opened for colonization only within the last several decades. The record of <em>T. fragilis</em> is biogeographically relevant, and constitutes an intermediate site between the species’ occurrences in the Antarctic Peninsula and southern South America. The present record of <em>B. nivale</em> is the fourth discovery of the species worldwide, which may be helpful for the future designation of the distribution of this extremely rare species.

Challenging the European southern refugium hypothesis: Species‐specific structures versus general patterns of genetic diversity and differentiation among small mammals

AbstractAimIn this study, we conduct a quantitative meta‐analysis to investigate broad patterns of genetic variation throughout large geographical regions in order to elucidate concordant geographical patterns across species and identify common historical processes to better inform the “cryptic refugia” versus the traditional “southern refugia” hypothesis debate.LocationEurope.Time periodLate Pleistocene to present day.Major taxa studiedSmall mammals (Rodentia, Eulipotyphla).MethodsA meta‐analysis was performed on large‐scale patterns of genetic diversity for 19 species from 59 papers. For each species, haplotype and nucleotide diversity were calculated using the mitochondrial D‐loop and compared to the species’ range.ResultsNo consistent patterns were observed between mitochondrial DNA (mtDNA) diversity indices (nucleotide and haplotype diversity) and any of the indicators of distribution examined [latitude and longitude (max, min, centre, range)]. The patterns of genetic diversity observed in all the 19 species studied appear to be species‐specific.Main conclusionsIn contrast to the traditional southern refugial hypotheses, we found no evidence for a consistent south–north post‐glacial expansion. Instead individual species appear to respond to climate oscillations in niche‐specific ways. This individual nature of each species’ phylogeographical history indicates a complex web of post‐glacial recolonization dynamics across Europe.

Mapping irrigated and rainfed wheat areas using high spatial–temporal resolution data generated by Moderate Resolution Imaging Spectroradiometer and Landsat

The detailed area and spatial distribution of irrigated and rainfed wheat can help forecast wheat yield and study water use efficiency. However, the similar spectral characteristics of irrigated and rainfed wheat make it difficult to separate them with low-spatial resolution or several high-spatial resolution images on the high heterogeneity of the southern Loess Plateau. To solve this challenge, this study used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced STARFM (ESTARFM) to generate time series of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI) at a 30-m resolution by fusing Moderate Resolution Imaging Spectroradiometer and Landsat data. Then, the phenological feature extracted from the predicted NDVI is combined with an auxiliary dataset to classify irrigated and rainfed wheat using the support vector machine classifier. An overall classification accuracy of 93.7% and a Kappa coefficient of 0.91 are achieved. Compared with corresponding high-resolution Google Earth images, the spatial distribution of the classification was consistent with actual land cover. This study demonstrates that the classification approach could classify irrigated and rainfed wheat in high heterogeneity regions and crops with smaller spectral characteristic differences. Moreover, it could be implemented across larger geographic regions

NOWCASTING EARTHQUAKES IN THE NORTHWEST HIMALAYA AND SURROUNDING REGIONS

Abstract. With the rapid increase and availability of seismic data, an automatic, transparent and regular way of earthquake hazard estimation strategy is highly desirable in many seismically active large geographical regions. In this paper, we implement a novel method of nowcasting (Rundle et al., 2016) that can indirectly assess the current progression of a region through its earthquake cycle of large events. Nowcasting differs from the method of forecasting in which future earthquake probabilities are calculated. Using statistics of natural times, counts of small earthquakes between large earthquakes in a defined region, nowcasting provides an earthquake potential score (EPS) to enable scientists and city planners a snapshot of the current level of earthquake hazard in the region. Applied to a number of selected major cities in the northwest Himalaya and surrounding regions, we found that the EPS values corresponding to M ≥ 6 events in New Delhi, Chandigarh, Dehradun and Shimla reach about 0.56, 0.87, 0.85 and 0.88, respectively. These estimated scores thus indicate that New Delhi is about half-way through its cycle for magnitude 6.0 or higher earthquakes, while Dehradun is about 85 percent of the way through its cycle. Towards the end, we discuss some implications and applications of these nowcast values to improve the present earthquake hazard assessment practice in the study region.

Phenotypic variations in the preferred host coral impact the occupancy of an obligate coral-dwelling fish.

Habitat specialists form tight relationships with their host habitat and are able to make microscale decisions when selecting final habitat locations. The obligate coral-dwelling fish, Gobiodon histrio, is thought to make habitat choices based on the coloration and structural characteristics of Acropora nasuta, their preferred coral host. Yet, most studies on the habitat preference of G. histrio have been conducted on Australia's Great Barrier Reef with no understanding if geographic differences in preferences exist. Here, we tested the habitat preference of G. histrio towards A. nasuta on the reefs of Kadavu and Tavewa Islands, Fiji. First, to assess the natural distribution, belt transect surveys of all acroporid corals were conducted. Transects indicated that, while G. histrio is most frequently found in A. nasuta over other acroporid corals, the coral's structural characteristics rather than the coral's color variation was the preferred characteristic. In contrast, the Australian G. histrio have been found to be more frequent in blue A. nasuta opposed to the brown color variation, suggesting a geographic difference in habitat preferences among the species. In addition, we conducted two in-situ behavioral field experiments to determine whether G. histrio would 1) move from dead A. nasuta to a live brown or blue A. nasuta and, 2) preferentially select between the brown or blue colored A. nasuta when placed on a dead A. nasuta. The results of the in-situ experiments support the finding that Fijian G. histrio does not discriminate between A. nasuta using color but uses only structural morphologies to guide its habitat selection process. Habitat selection is a complex process, and microscale habitat preferences within a species can vary between geographic locations. This study sheds light on the need to expand research findings to incorporate large geographic regions when attempting to understand the preferences of coral reef symbionts.

A high-throughput system used to determine frequency and distribution of phosphine resistance across large geographical regions.

Next-generation sequencing can enable genetic surveys of large numbers of individuals. We developed a genotyping-by-sequencing assay for detecting strong phosphine resistance alleles in the dihydrolipoamide dehydrogenase (dld) gene of Rhyzopertha dominica populations. The assay can estimate the distribution and frequency of resistance variants in thousands of individual insects in a single run. We analysed 1435 individual insects collected over a 1-year period from 59 grain-storage sites including farms (n=29) and central storages (n=30) across eastern Australia. Resistance alleles were detected in 49% of samples, 38% of farms and 60% of central storages. Although multiple alleles were detected, only two resistance variants (P49S and K142E) were widespread and each appeared to have a distinct but overlapping geographical distribution. The type of structure in which the grain is stored had a strong effect on resistance allele frequency. We observed higher frequencies of resistance alleles in bunker storages at central sites compared with other storage types. This contributed to the higher frequencies of resistance alleles in bulk-handling facilities relative to farms. The discovery of a storage structure that predisposes insects to resistance highlights the utility of our high-throughput assay system for improvement of phosphine resistance management practices. © 2018 Society of Chemical Industry.

Elimination of 72-Hour Quantitative Fecal Fat Testing by Restriction, Laboratory Consultation, and Evaluation of Specimen Weight and Fat Globules.

The 72-h quantitative fecal fat test has been mostly obsolete for many years. Our objective was to reduce and eliminate the use of this test, while providing suitable alternatives. We assessed (2010-2016) utilization of the fecal fat test in Calgary, Central Alberta, and Southern Alberta, Canada. Alternatives were identified through literature review and consultation with gastroenterologist stakeholders. Logistic regression and ROC curves were used to characterize discrimination power of 72-h specimen weight on abnormal fat excretion. This was also examined in 91 subspecimens that were additionally tested for the presence of fat globules. As 69% of fecal fat tests (total, 106/year) were on adults (age ≥ 18), stakeholders agreed that adult specimens should not be tested until ordering physicians consulted with a clinical biochemist. This change reduced fecal fat testing by 81% to 20/year in 2015. The 72-h specimen weight was a significant predictor of abnormal fat excretion [P < 0.001; area under curve (AUC) = 0.75-0.79, n = 115-417] in historic fecal fat data. A similar result was observed among subspecimens (AUC = 0.70), which improved when additionally considering the presence of fat globules (AUC = 0.74). Stakeholders consented to replacing fecal fat with a comparison of specimen weight to cutpoints with 80% specificity for abnormal fat excretion, and the test for fat globules. Through stakeholder engagement, we implemented changes that eliminated 72-h quantitative fecal fat testing in a large geographic region in Alberta, Canada. Future fecal fat orders would be reflexed to an assessment of 72-h specimen weight and a qualitative test for fat globules in stool.

The burden of Parkinson's disease: a worldwide perspective

The burden of Parkinson's disease: a worldwide perspective

A dynamic agricultural prediction system for large-scale drought assessment on the Sunway TaihuLight supercomputer

Crop models are widely used to evaluate the response of crop growth to drought. However, over large geographic regions, the most advanced models are often restricted by available computing resource. This limits capacity to undertake uncertainty analysis and prohibits the use of models in real-time ensemble forecasting systems. This study addresses these concerns by presenting an integrated system for the dynamic prediction and assessment of agricultural yield using the top-ranked Sunway TaihuLight supercomputer platform. This system enables parallelization and acceleration for the existing AquaCrop, DNDC (DeNitrification and DeComposition) and SWAP (Soil Water Atmosphere Plant) models, thus facilitating multi-model ensemble and parameter optimization and subsequent drought risk analysis in multiple regions and at multiple scales. The high computing capability also opens up the possibility of real-time simulation during droughts, providing the basis for more effective drought management. Initial testing with varying core group numbers shows that computation time can be reduced by between 2.6 and 3.6 times. Based on the powerful computing capacity, a county-level model parameter optimization (2043 counties for 1996–2007) by Bayesian inference and multi-model ensemble using BMA (Bayesian Model Average) method were performed, demonstrating the enhancements in predictive accuracy that can be achieved. An application of this system is presented predicting the impacts of the drought of May–July 2017 on maize yield in North and Northeast China. The spatial variability in yield losses is presented demonstrating new capability to provide high resolution information with associated uncertainty estimates.

Spatially Explicit, Regional‐Scale Simulation of Lake Carbon Fluxes

AbstractLakes are areas of intense biogeochemical processing in the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. However, current large‐scale estimates of lake biogeochemical fluxes are all generated by multiplying a mean observed areal rate by regional or global lake surface area, which ignores important heterogeneous spatial and temporal processes that regulate lake carbon cycling. We have developed a process‐based model that integrates core scientific knowledge in hydrology, biogeochemistry, and ecology that is specifically designed to be applied over large geographic regions to hindcast or forecast regional lake carbon fluxes. We used our model to simulate daily carbon fluxes and pools for 3,675 lakes in the Northern Highlands Lake District from 1980–2010 and produced spatial and seasonal patterns consistent with observations. Variabilities in lake carbon fluxes were well predicted by relatively simple hydrologic metrics, such as the fraction of hydrologic export as evaporation (FHEE). Overall, lakes with a high FHEE processed a greater percentage of carbon inputs in the simulations than lakes with a low FHEE, but low‐FHEE lakes ultimately processed more total carbon because of greater carbon inputs. Large lakes with low FHEE and high external loading of dissolved inorganic carbon contributed most to total CO2 emissions for the Northern Highlands Lake District, and our model estimated that 78% of total CO2 emissions from lakes to the atmosphere originated from external loads of dissolved inorganic carbon. By better characterizing the unique biogeochemical processes for each individual lake, regional estimates of carbon fluxes are more accurately determined.

Lost in Aggregation: The Geographic Distribution of Kwashiorkor in Eastern Democratic Republic of the Congo.

Kwashiorkor is a major classification of severe acute malnutrition whose etiology remains elusive. It is estimated to affect hundreds of thousands of children annually, but no accurate global prevalence figures are available. Little is known how prevalence varies within populations, an important undocumented aspect of kwashiorkor obscured by the aggregation of prevalence or incidence of the condition across large populations and geographic areas. To estimate the prevalence of kwashiorkor in select neighboring villages of the eastern Democratic Republic of the Congo (DRC) and assess if prevalence can vary dramatically among neighboring villages. An anthropometric census survey evaluated 1328 children aged 12 to 59 months within all 19 villages in one health area of eastern DRC, recording all cases of kwashiorkor, diagnosed by bipedal pitting edema. Village-level prevalence of kwashiorkor in the study area varied from 0% to 14.9%. Interviews with health services staff in the study area and across 2 provinces confirmed that current differences in prevalence reflect a long-term pattern and are a common feature of kwashiorkor throughout this region. Aggregation of kwashiorkor prevalence and incidence data across large populations or geographic regions poses several risks to understanding the epidemiology of kwashiorkor. If clustering of kwashiorkor is not taken into account, (1) nutritional crises in particular villages may go undetected; (2) the real effect of interventions may be underestimated; (3) interventions may be inappropriately targeted, leading to reduced coverage, efficacy, and cost-efficiency; and (4) important insights into the root causes of kwashiorkor may be lost.

The effect of distance on short-term outcomes in a regionalized, publicly funded bariatric surgery model.

While high-volume Centers of Excellence (COE) for bariatric surgery may have improved clinical outcomes, their disparate distribution results in longer travel distances for patients. The purpose of this study was to investigate effect of distance from COE on outcomes and readmission. This was a retrospective study of alladults,aged 18 years or older, receiving bariatric surgery from April 2009 to March 2012 in the province of Ontario. Main outcomes included 30-day complication rates and readmission. Multivariable logistic regression was used to examine the impact of distance from patients' primary residence to their bariatric COE on patient outcomes and readmissions. Five thousand and seven patients were identified, two-thirds residing within 100km of a COE with a mean distance of 117.2km. The majority of patients did not reside within a Local Integrated Health Network (LHIN) that contained a COE, while 18.3% of patients lived in rural areas. Using multivariable adjustment, for every 10km increase from the COE where surgery was performed, the Odds Ratio (OR) for complications was 1.00 [95% Confidence Interval (CI) 0.99-1.01; P = 0.747]. Additionally, both residing in a LHIN without a COE, OR 1.10 (95% CI 0.87-1.40; P = 0.434), and rural status, OR 0.97 (95% CI 0.77-1.23; P = 0.821) showed no increase in risk of complication. Similarly, further distances did not influence rate of readmission, OR 0.99 (95% CI 0.98-1.00; P = 0.077) nor did rural status OR 1.31 (95% CI 0.97-1.76; P = 0.076). The COE model, where a few centers in high population areas service a large geographic region, is adequate in ensuring patients that livefurther away receive appropriate short-term care.

Modelling current and future abundances of benthic invertebrates using bathymetric LiDAR and oceanographic variables

AbstractA key requirement for managing commercial fisheries is understanding the geographic footprint of the resource, the level of exploitation and the potential impacts of changing climate or habitat conditions. The development of spatially explicit predictive models of species distributions combined with predictions of changing oceanographic conditions provides the opportunity to obtain new insights of species‐habitat associations. Here, generalized linear models (GLMs) were used to model the abundance of two commercially important marine macro‐invertebrates, blacklip abalone Haliotis rubra and long‐spined sea urchin Centrostephanus rodgersii, along the coast of Victoria, Australia. We combined abundance data from fisheries independent diver surveys with environmental variables derived from bathymetric light detection and ranging (LiDAR) and oceanographic parameters derived from satellite imagery. The GLM was used to predict species responses to environmental gradients where reef complexity, sea surface temperature (SST) and depth were strongly associated with species distributions. The abundance of H. rubra declined with increasing summer SST. In comparison, the abundance of C. rodgersii increased with increasing winter SST. The GLM showed that the projected increase in ocean temperatures will likely lead to a decline in abundance across the H. rubra fishery. Conversely, a range expansion of C. rodgersii is likely due to the strengthening of the East Australian Current. For species that exhibit a high affinity to specific seascape features, this research demonstrated how recent advances in seabed mapping can allow the identification of areas with high conservation or fisheries value at a fine‐scale relevant to resource exploitation across large geographic regions.

Enhancing Chemotherapy Capabilities in Rural Hospitals: Implementation of a Telechemotherapy Model (QReCS) in North Queensland, Australia.

The Queensland Remote Chemotherapy Supervision (QReCS) model enables rural nurses to administer chemotherapy in smaller rural towns under supervision by health professionals from larger centers using telehealth. Its implementation began in North Queensland, Australia (population, 650,000), in 2014 between two regional cancer centers (Townsville and Cairns as primary sites) and six rural sites (125 to 1,000 kilometers from primary sites). Our study examined the implementation processes, feasibility, and safety of this model. Details of implementation and patients' clinical details for the period of 2014 to 2016 for descriptive analysis were extracted from telechemotherapy project notes and oncology information systems of North Queensland, respectively. After a successful pilot study in Townsville Cancer Centre, statewide rural and cancer networks of Queensland Health, in collaboration with clinicians and managers across the state of Queensland, developed the QReCS model and a guide for operationalizing it. QReCS was implemented at six sites from 2014 to 2016. Main enablers across North Queensland included collaboration among clinicians and managers, availability of common electronic medical records, funding from Queensland Health, and installation of telehealth infrastructure by statewide telehealth services. Main barriers included turnover of senior management and nursing staff at two rural towns. Sixty-two patients received 327 cycles of low- to medium-risk chemotherapy agents. Rates of treatment delays, adverse events, and hospital admissions were similar to those in face-to-face care. Implementation of the QReCS model across a large geographic region is feasible with acceptable safety profiles. Leadership by and collaboration among clinicians and managers, adequacy of resources and common governance are key enablers.

Performance-based multi-hazard topology optimization of wind and seismically excited structural systems

The integration of topology optimization procedures into modern structural design frameworks is gaining interest as an innovative approach for achieving more efficient designs. To this end, probabilistic performance-based topology optimization frameworks have recently been proposed for the identification of optimal structural systems subject to extreme wind or seismic events considered in isolation. However, there are large geographic regions that are subject to both wind and seismic hazards. Therefore, the development of methods that can ensure that target performance metrics are met within a multi-hazard setting is a crucial step towards improving the reliability of structural systems.This paper is focused on proposing a simulation-centered performance-based topology optimization framework for the identification of optimal structural systems for multi-hazard wind and seismic environments. A probabilistic performance assessment framework is firstly proposed based on synergistically describing the performance of wind or seismically excited systems. Based on this framework, a multi-hazard topology optimization strategy is proposed. In particular, the methodology is centered on the definition of an approximate optimization sub-problem that not only decouples the simulation-based performance assessment from the optimization loop, but also transforms the dynamic and uncertain optimization problem into an explicit static and deterministic problem therefore enabling its efficient resolution using any gradient-based optimizer. Optimal lateral load resisting systems that rigorously meet the probabilistic performance constraints set within the multi-hazard environment are therefore identified. A case study is presented demonstrating the potential of the proposed framework.

D-FROST: Distributed Frequency Reuse-Based Opportunistic Spectrum Trading via Matching With Evolving Preferences

Spectrum trading creates more accessing opportunities for secondary users (SUs), and economically benefits the primary users (PUs). Compared with centralized spectrum trading designs, e.g., spectrum auction, distributed spectrum trading captures instantaneous spectrum trading opportunities better over large geographical regions without incurring extra infrastructure deployment and has no network scalability issues. However, the existing distributed spectrum trading designs have limited concern regarding spectrum reuse. Considering spatial reuse, in this paper, we propose a novel distributed frequency reuse-based opportunistic spectrum trading (D-FROST) scheme, which can further improve spectrum utilization, provide more accessing opportunities for SUs, and increase the revenues of PUs. In this paper, we employ conflict graph to characterize the SUs’ co-channel and radio interferences, and mathematically formulate a centralized PUs’ revenue maximization problem under multiple wireless transmission constraints. Due to the NP-hardness to solve the problem and the non-existence of centralized trading entity, we develop the D-FROST algorithms based on matching with evolving preferences, and prove its stability. Through extensive simulations, we show that the proposed D-FROST algorithm is superior to other distributed spectrum trading algorithms without considering spectrum reuse, yields results close to the centralized optimal one, and is effective in increasing PUs’ revenue and improving spectrum utilization.

Pathological evidence reveals cattle traction in North China by the early second millennium BC

The use of cattle labour in antiquity is a worldwide well-discussed topic among researchers as it can shed light on the possible development trajectories of our communities over the past several millennia. Zooarchaeology can play a vital role in illuminating the history of cattle traction through observed pathologies on cattle bones linked to traction activity. Systemic zooarchaeological investigation is still underdeveloped in China, one of the likely early beneficiaries of animal labour exploitation in the world. Here, we apply the pathological index (PI) method, first developed by Bartosiewicz et al. on European assemblages, to Chinese Bronze Age cattle bones. Our results first confirm the wide applicability of the PI method with the involvement of Chinese control samples, which holds the potential to be applied as an effective tool in a larger geographical region. Our results also confirm the importance of cattle traction for the Late Shang states ( c. 1300–1046 BC) as previously proposed on the basis of disputed interpretations of oracle bone inscriptions as showing cattle ploughing, but also show that light cattle traction practices likely developed in China in the Bronze Age Erlitou ( c. 1750–1530 BC) and Early Shang ( c. 1600–1300 BC) periods. Cattle traction use in the Chinese Bronze Age may have facilitated the introduction and subsequent cultivation in China of wheat, an exotic cereal.

Representing a large region with few sites: The Quality Index approach for field studies

Many environmental studies require the characterization of a large geographical region using a range of representative sites amenable to intensive study. A systematic approach to selecting study areas can help ensure that an adequate range of the variables of interest is captured. We present a novel method of selecting study sites representing a larger region, in which the region is divided into subregions, which are characterized with relevant independent variables, and displayed in mathematical variable space. Potential study sites are also displayed this way, and selected to cover the range in variables present in the region. The coverage of sites is assessed with the Quality Index, which compares the range and standard deviation of variables among the sites to that of the larger region, and prioritizes sites that are well-distributed (i.e. not clumped) in variable space. We illustrate the method with a case study examining relationships between agricultural land use, physiography and stream phosphorus (P) export, in which we selected several variables representing agricultural P inputs and landscape susceptibility to P loss. A geographic area of 110,000km2 was represented with 11 study sites with good coverage of four variables representing agricultural P inputs and transport mechanisms taken from commonly-available geospatial datasets. We use a genetic algorithm to select 11 sites with the highest possible QI and compare these, post-hoc, to our sites. This approach reduces subjectivity in site selection, considers practical constraints and easily allows for site reselection if necessary. This site selection approach can easily be adapted to different landscapes and study goals, as we provide an algorithm and computer code to reproduce our approach elsewhere.

Determining a geographic high resolution supply chain network for a large scale biofuel industry

This research combines Geographic Information Systems (GIS) and Mixed Integer Programming (MIP) model to determine feedstock supply, preprocessing facility, and biorefinery locations at a highly resolved spatial scale with the objective of meeting a large-scale annual biofuel production and demand goal for Tennessee, USA. Simultaneous determination of this supply chain network using MIP is computationally expensive. Memory limitation of typical personal computers constrain the network problem. High Performance Computing environments may require days to solve, and without any assurance of a feasible solution. This paper proposes a two-stage optimization procedure to overcome these computational challenges while maintaining theoretical consistency with conventional firm location theory paradigms. The two-stage procedure assumes that firms first identify biorefinery locations with comparative advantage in terms of supplying biomass. Step two entails determining if costs can be lowered with the addition of preprocessing facilities, and their optimal location relative to the biorefinery sites. In contrast, a single step optimization procedure siting multiple biorefineries and concomitantly preprocessing units and biomass supply areas assumes a different strategy for a single firm. Results suggest that the two-stage optimization approach is able to identify a feasible solution of multiple feedstock areas, feedstock preprocessing and fuel production locations using high-resolution spatial layers over a relatively large geographic region in a fraction of the computer resources required to solve a single, simultaneous location problem. The optimal supply chain network solutions generated from the two-stage and single simultaneous approaches are different. The absolute difference in the smaller scaled models’ objective values is less than 1%.