Skip to main content

Advertisement

SpringerLink
Log in

Natural Resources Research Publications on Resourcing Future Generations, and Introduction of Papers in this Special Issue

  • Review Paper
  • Published:
Natural Resources Research Aims and scope Submit manuscript

Abstract

The Journal of Natural Resources Research (NRR) has, since its foundation in 1992, published and continues to publish peer-reviewed articles that make significant impact on resourcing future generations. This is in keeping with its aims and scope of publishing articles on quantitative analyses of natural (mainly but not limited to mineral) resources with regard to exploration, evaluation and exploitation, as well as environmental and risk-related aspects. However, the new papers introduced in this special issue of NRR are mostly qualitative studies with implications for policy decision-making relevant to the issue of resourcing future generations. These new papers and the recent inclusion of NRR for coverage in the Science Citation Index Expanded™ (or SciSearch®) and Journal Citation Reports® (JCR) Science Edition will make NRR more attractive to researchers in the fields that are relevant to the issue of resourcing future generations, both as a source of knowledge as well as a medium for publication of research results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Google Scholar (http://scholar.google.com) is an Internet search engine for scholarly information including journal articles, conference papers, theses, technical reports and books. The numbers of citations mentioned in the text per paper were current on the day the proof of this article was approved.

References

From NRR: Papers concerning resource demand

  • Attanasi, E. D., & Freeman, P. A. (2012). Role of stranded gas from central Asia and Russia in meeting Europe’s future import demand for gas. Natural Resources Research, 21, 193–220.

    Article  Google Scholar 

  • Edmonson, N. (1994). Industrial sulfur demand: Analysis and prospect. Nonrenewable Resources, 3, 205–215.

    Article  Google Scholar 

  • Ewusi, A., & Kuma, J. S. (2014). Groundwater assessment for current and future water demand in the Daka Catchment, Northern Region, Ghana. Natural Resources Research, 23, 355–365.

    Article  Google Scholar 

  • Feygin, M. V., & Ryzhik, V. M. (2001). Estimation of the oil reserves requirement to meet a given production level—mathematical modeling. Natural Resources Research, 10, 51–58.

    Article  Google Scholar 

  • Herring, J. R., & Fantel, R. J. (1993). Phosphate rock demand into the next century: impact on world food supply. Nonrenewable Resources, 2, 226–246.

    Article  Google Scholar 

  • Nishiyama, T. (1996). Trends and short-term prospects for copper demand. Nonrenewable Resources, 5, 155–168.

    Article  Google Scholar 

  • Pan, G., & Harris, D. P. (1993). The latest trend tracing model for projection of mineral demand. Nonrenewable Resources, 2, 31–38.

    Article  Google Scholar 

  • Patiño-Douce, A. E. (2016). Metallic mineral resources in the twenty-first century. I. Historical extraction trends and expected demand. Natural Resources Research, 25, 71–90.

    Article  Google Scholar 

  • Pariente-David, S. (1998). The future of global oil demand and the growing role of the transport sector. Nonrenewable Resources, 7, 129–135.

    Article  Google Scholar 

  • Sophocleous, M. (2004). Global and regional water availability and demand: Prospects for the future. Natural Resources Research, 13, 61–75.

    Article  Google Scholar 

  • Suslick, S. B. (1998). Factor analysis of trends in energy and metals production and consumption in developed and developing countries. Nonrenewable Resources, 7, 211–224.

    Article  Google Scholar 

  • Youngquist, W., & Duncan, R. C. (2003). North American natural gas: Data show supply problems. Natural Resources Research, 12, 229–240.

    Article  Google Scholar 

From NRR: Papers concerning assessment of discovered resources

  • Agterberg, F. P. (1993). Calculation of the variance of mean values for blocks in regional resource evaluation studies. Nonrenewable Resources, 2, 312–324.

    Article  Google Scholar 

  • Anderson, M., & Gullco, R. S. (2001). Probability estimates of field areas and trapped oil volumes. Natural Resources Research, 10, 149–158.

    Article  Google Scholar 

  • Attanasi, E. D. (2001). Geologic coal assessment: The interface with economics. Natural Resources Research, 10, 189–195.

    Article  Google Scholar 

  • Attanasi, E. D., & Coburn, T. C. (2004). A bootstrap approach to computing uncertainty in inferred oil and gas reserve estimates. Natural Resources Research, 13, 45–52.

    Article  Google Scholar 

  • Attanasi, E. D., & Coburn, T. C. (2009). Evaluation of procedures for prediction of unconventional gas in the presence of geologic trends. Natural Resources Research, 18, 153–171.

    Article  Google Scholar 

  • Attanasi, E. D., Coburn, T. C., & Freeman, P. A. (2006). Prediction of resource volumes at untested locations using simple local prediction models. Natural Resources Research, 15, 223–239.

    Article  Google Scholar 

  • Attanasi, E. D., & Schmoker, J. W. (1997). Long-term implications of new US gas estimates. Nonrenewable Resources, 6, 53–62.

    Article  Google Scholar 

  • Bartsch-Winkler, S., Sutphin, D. M., Ball, M. M., Korzeb, S. L., Kness, R. F., & Dutchover, J. T. (1993). Summary of the mineral-and energy-resource endowment, BLM Roswell resource area, east-central New Mexico. Nonrenewable Resources, 2, 262–283.

    Article  Google Scholar 

  • Blackwell, D. D., Negraru, P. T., & Richards, M. C. (2006). Assessment of the enhanced geothermal system resource base of the United States. Natural Resources Research, 15, 283–308.

    Article  Google Scholar 

  • Carr, J. R. (1992). A treatise on the use of geostatistics for the characterization of nonrenewable resources. Nonrenewable Resources, 1, 61–73.

    Article  Google Scholar 

  • Chaves, H. A., & Effie Lewis, M. (1994). From data gathering to resources assessment: A holistic view of petroleum geology. Nonrenewable Resources, 3, 72–82.

    Article  Google Scholar 

  • Chen, Z., & Sinding-Larsen, R. (1999). Estimating petroleum resources using geo-anchored method—a sensitivity study. Natural Resources Research, 8, 49–58.

    Article  Google Scholar 

  • Crovelli, R. A., Schmoker, J. W., & Balay, R. H. (1997). US department of the interior US geological survey: Fractal lognormal percentage analysis of the US geological survey’s 1995 national assessment of conventional oil and gas resources. Nonrenewable Resources, 6, 43–51.

    Article  Google Scholar 

  • De Souza, L., Costa, J. C., & Koppe, J. C. (2004). Uncertainty estimate in resources assessment: A geostatistical contribution. Natural Resources Research, 13, 1–15.

    Article  Google Scholar 

  • Drew, L. J., & Menzie, W. D. (1993). Is there a metric for mineral deposit occurrence probabilities? Nonrenewable Resources, 2, 92–105.

    Article  Google Scholar 

  • Drew, L. J., & Schuenemeyer, J. H. (1997). Oil-and gas-resource assessment in certain South American Basins—an application of ARDS (Ver. 5.0) to complex exploration and discovery histories. Nonrenewable Resources, 6, 295–315.

    Article  Google Scholar 

  • Dyni, J. R., Wiig, S. V., & Grundy, W. D. (1995). Trona resources in southwest Wyoming. Nonrenewable Resources, 4, 340–352.

    Article  Google Scholar 

  • Finch, W. I., Grundy, W. D., & Pierson, C. T. (1992). Statistical sampling of the distribution of uranium deposits using geologic/geographic clusters. Nonrenewable Resources, 1, 148–152.

    Article  Google Scholar 

  • Gettings, M. E. (2013). Monte Carlo simulations of product distributions and contained metal estimates. Natural Resources Research, 22, 239–254.

    Article  Google Scholar 

  • Gill, D. (1992). Israel’s petroleum discovery curve. Nonrenewable Resources, 1, 231–238.

    Article  Google Scholar 

  • Griffiths, J. C., Pilant, A. D., & Smith, C. M. (1997). Quantitative estimates of the geology of large regions and their application to mineral-resource assessment. Nonrenewable Resources, 6, 157–236.

    Article  Google Scholar 

  • Grunsky, E. C., Kilby, W. E., & Massey, N. W. (1994). Mineral resource assessment in British Columbia. Nonrenewable Resources, 3, 271–283.

    Article  Google Scholar 

  • Gunther, T. M. (1992). Quantitative assessment of future development of copper/silver resources in the Kootenai National Forest, Idaho/Montana: Part II—Economic and policy analysis. Nonrenewable Resources, 1, 267–280.

    Article  Google Scholar 

  • Hall, S. M. (2013). Review of the NURE assessment of the US Gulf Coast uranium province. Natural Resources Research, 22, 255–272.

    Article  Google Scholar 

  • Harff, J., Davis, J. C., & Olea, R. A. (1992). Quantitative assessment of mineral resources with an application to petroleum geology. Nonrenewable Resources, 1, 74–84.

    Article  Google Scholar 

  • Harris, D., & Pan, G. (1993). Intrinsic sample methods for mineral exploration and resource assessment. Nonrenewable Resources, 2, 113–121.

    Article  Google Scholar 

  • Hower, J. C., Hiett, J. K., Wild, G. D., & Eble, C. F. (1994). Coal resources, production, and quality in the Eastern Kentucky Coal Field: Perspectives on the future of steam coal production. Nonrenewable Resources, 3, 216–236.

    Article  Google Scholar 

  • Koike, K., Minta, T., Ishizaka, S., & Ohmi, M. (1996). Hydrogeological and ground-water resource analysis using a geotechnical database. Nonrenewable Resources, 5, 23–32.

    Article  Google Scholar 

  • Lee, P. J., & Singer, D. A. (1994). Using PETRIMES to estimate mercury deposits in California. Nonrenewable Resources, 3, 190–199.

    Article  Google Scholar 

  • Levchenko, I. V. (1994). A data base on occurrences of gold in Central Asia and its application. Nonrenewable Resources, 3, 96–108.

    Article  Google Scholar 

  • Meneley, R. A. (2005). Assessment methodology and results from the Canadian Gas Potential Committee 2001 report. Natural Resources Research, 14, 153–173.

    Article  Google Scholar 

  • Meyer, F. M. (2004). Availability of bauxite reserves. Natural Resources Research, 13, 161–172.

    Article  Google Scholar 

  • Nederlof, M. H. (1994). Comparing probabilistic predictions with outcomes in petroleum exploration prospect appraisal. Nonrenewable Resources, 3, 183–189.

    Article  Google Scholar 

  • Olea, R. A. (2011). On the use of the beta distribution in probabilistic resource assessments. Natural Resources Research, 20, 377–388.

    Article  Google Scholar 

  • Pan, G., Harris, D. P., & Heiner, T. (1992). Fundamental issues in quantitative estimation of mineral resources. Nonrenewable Resources, 1, 281–292.

    Article  Google Scholar 

  • Pan, R., & Ma, X. (1997). An approach to reserve estimation enhanced with 3-D seismic data. Nonrenewable Resources, 6, 251–255.

    Article  Google Scholar 

  • Rehder, S., & Franke, D. (2012). How to include ignorance into hydrocarbon-resource assessments? A case study applied to the presence of source rock at the Argentine Deep Water Margin. Natural Resources Research, 21, 301–309.

    Article  Google Scholar 

  • Root, D. H., Menzie, W. D., & Scott, W. A. (1992). Computer Monte Carlo simulation in quantitative resource estimation. Nonrenewable Resources, 1, 125–138.

    Article  Google Scholar 

  • Salazar, J., McVay, D. A., & Lee, W. J. (2010). Development of an improved methodology to assess potential unconventional gas resources. Natural Resources Research, 19, 253–268.

    Article  Google Scholar 

  • Schuenemeyer, J. H. (2002). A framework for expert judgment to assess oil and gas resources. Natural Resources Research, 11, 97–107.

    Article  Google Scholar 

  • Shields, D. J., & Todd, S. W. (1998). Using logistic regression to merge mineral resource databases. Nonrenewable Resources, 7, 53–61.

    Article  Google Scholar 

  • Shulman, M., Burger, H., Kliem, C., & Skala, W. (1992). Review of resource analysis and related studies: Working group, Mathematical Geology, Freie Universität Berlin. Nonrenewable Resources, 1, 97–106.

    Article  Google Scholar 

  • Simon, J. L., Weinrauch, G., & Moore, S. (1994). The reserves of extracted resources: Historical data. Nonrenewable Resources, 3, 325–340.

    Article  Google Scholar 

  • Sirotinskaya, S. V. (2004). Cause-effect analysis in assessment of mineral resources. Natural Resources Research, 13, 17–28.

    Article  Google Scholar 

  • Spanski, G. T. (1992). Quantitative assessment of future development of cooper/silver resources in the Kootenai National Forest, Idaho/Montana: Part I—estimation of the copper and silver endowments. Nonrenewable Resources, 1, 163–183.

    Article  Google Scholar 

  • Stueck, H., Houseknecht, D., Franke, D., Gautier, D., Bahr, A., & Ladage, S. (2016). Shale-gas assessment: Comparison of gas-in-place versus performance-based approaches. Natural Resources Research, 25, 315–329.

    Article  Google Scholar 

  • Wang, Y., Tan, B., Wang, Y., & Wu, J. (1994). Information structure analysis for quantitative assessment of mineral resources and the discovery of a silver deposit. Nonrenewable Resources, 3, 284–294.

    Article  Google Scholar 

  • Xu, J., Liu, X., Chen, Z., & Gao, C. (1997). A probabilistic method for resource appraisal in a petroleum play and its application. Nonrenewable Resources, 6, 277–280.

    Article  Google Scholar 

  • Yamamoto, J. K. (1999). Quantification of uncertainty in ore-reserve estimation: Applications to Chapada copper deposit, State of Goiás, Brazil. Natural Resources Research, 8, 153–163.

    Article  Google Scholar 

  • Zhao, P., Chen, J., Chen, J., Zhang, S., & Chen, Y. (2005). The “Three-Component” digital prospecting method: A new approach for mineral resource quantitative prediction and assessment. Natural Resources Research, 14, 295–303.

    Article  Google Scholar 

From NRR: Papers concerning estimation of undiscovered resources

  • Ahlbrandt, T. S., & Klett, T. R. (2005). Comparison of methods used to estimate conventional undiscovered petroleum resources: World examples. Natural Resources Research, 14, 187–210.

    Article  Google Scholar 

  • Brew, D. A., Drew, L. J., & Ludington, S. D. (1992). The study of the undiscovered mineral resources of the Tongass National Forest and adjacent lands, southeastern Alaska. Nonrenewable Resources, 1, 303–322.

    Article  Google Scholar 

  • Carranza, E. J. M. (2017). Natural resources research publications on geochemical anomaly and mineral potential mapping, and introduction to the special issue of papers in these fields. Natural Resources Research, 26, 379–410.

    Article  Google Scholar 

  • Charpentier, R. R., Dolton, G. L., & Ulmishek, G. F. (1995). Annotated bibliography of methodology for assessment of undiscovered oil and gas resources. Nonrenewable Resources, 4, 154–186.

    Article  Google Scholar 

  • Charpentier, R. R., & Klett, T. R. (2005). Guiding principles of USGS methodology for assessment of undiscovered conventional oil and gas resources. Natural Resources Research, 14, 175–186.

    Article  Google Scholar 

  • Chen, Z., & Sinding-Larsen, R. (1994a). Discovery process modeling—a sensitivity study. Nonrenewable Resources, 3, 295–303.

    Article  Google Scholar 

  • Chen, Z., & Sinding-Larsen, R. (1994b). Estimating number and field size distribution in frontier sedimentary basins using a Pareto model. Nonrenewable Resources, 3, 91–95.

    Article  Google Scholar 

  • Chen, Z., Sinding-Larsen, R., & Ma, X. (1997a). Application of discovery process models in estimating petroleum resources at the play level in China. Nonrenewable Resources, 6, 317–328.

    Article  Google Scholar 

  • Chenglin, L., & Charpentier, R. R. (2010). Quality of the log-geometric distribution extrapolation for smaller undiscovered oil and gas pool size. Natural Resources Research, 19(1), 11–21.

    Article  Google Scholar 

  • Cox, D. P. (1993). Estimation of undiscovered deposits in quantitative mineral resource assessments—examples from Venezuela and Puerto Rico. Nonrenewable Resources, 2, 82–91.

    Article  Google Scholar 

  • Crovelli, R. A. (1992). Probabilistic methodology for estimation of undiscovered petroleum resources in play analysis of the United States. Nonrenewable Resources, 1, 153–162.

    Article  Google Scholar 

  • Crovelli, R. A. (1995). The generalized 20/80 law using probabilistic fractals applied to petroleum field size. Nonrenewable Resources, 4, 233–241.

    Article  Google Scholar 

  • Drew, L. J., & Schuenemeyer, J. H. (1992). A petroleum discovery-rate forecast revisited—the problem of field growth. Nonrenewable Resources, 1, 51–60.

    Article  Google Scholar 

  • Drew, L. J., & Schuenemeyer, J. H. (1996). Oil and gas resource assessment: the linkage between geological analysis and discovery process model results. Nonrenewable Resources, 5, 33–42.

    Article  Google Scholar 

  • Drew, L. J., Schuenemeyer, J. H., & Mast, R. F. (1995). Application of the modified Arps-Roberts discovery process model to the 1995 US National Oil and Gas Assessment. Nonrenewable Resources, 4, 242–252.

    Article  Google Scholar 

  • Dyman, T. S., Crovelli, R. A., Bartberger, C. E., & Takahashi, K. I. (2002). Worldwide estimates of deep natural gas resources based on the US Geological Survey World Petroleum Assessment 2000. Natural Resources Research, 11, 207–218.

    Article  Google Scholar 

  • Dyman, T. S., Wyman, R. E., Kuuskraa, V. A., Lewan, M. D., & Cook, T. A. (2003). Deep natural gas resources. Natural Resources Research, 12, 41–56.

    Article  Google Scholar 

  • Feygin, M. (2002). Correlation between oil production and reserves discovery. Natural Resources Research, 11, 121–124.

    Article  Google Scholar 

  • Forman, D. J., & Hinde, A. L. (1996). Correlation between assessments of undiscovered oil and gas resources. Nonrenewable Resources, 5, 43–52.

    Article  Google Scholar 

  • Forman, D. J., Hinde, A. L., & Cadman, S. J. (1995). Use of closure area and resources per unit area for assessing undiscovered petroleum resources in part of the Cooper Basin, South Australia. Nonrenewable Resources, 4, 60–73.

    Article  Google Scholar 

  • Kaufman, G. M. (2005). Where have we been? Where are we going? Natural Resources Research, 14, 45–152.

    Article  Google Scholar 

  • Lisitsin, V. A. (2016). Rank-size statistical assessments of undiscovered gold endowment in the Bendigo and Stawell Zones (Victoria) and the Mossman Orogen (Queensland), Australia: Comparison with three-part assessment results. Natural Resources Research, 25, 269–282.

    Article  Google Scholar 

  • Logan, K. G. (2005). The truncated discovery process model. Natural Resources Research, 14, 265–281.

    Article  Google Scholar 

  • McCammon, R. B. (2003). Estimates of number of undiscovered deposits of gold, silver, copper, lead, and zinc in the United States. Natural Resources Research, 12, 67–78.

    Article  Google Scholar 

  • McCammon, R. B., & Finch, W. I. (1993). The deposit size frequency method for estimating undiscovered uranium deposits. Nonrenewable Resources, 2, 106–112.

    Article  Google Scholar 

  • McCammon, R. B., Finch, W. I., Kork, J. O., & Bridges, N. J. (1994). An integrated data-directed numerical method for estimating the undiscovered mineral endowment in a region. Nonrenewable Resources, 3, 109–122.

    Article  Google Scholar 

  • McCammon, R. B., & Kork, J. O. (1992). One-level prediction—a numerical method for estimating undiscovered metal endowment. Nonrenewable Resources, 1, 139–147.

    Article  Google Scholar 

  • McCammon, R. B., Root, D. H., & Schruben, P. G. (2004). Statewide estimates of undiscovered deposits of gold, silver, copper, lead, and zinc. Natural Resources Research, 13, 201–207.

    Article  Google Scholar 

  • Merriam, D. F., Drew, L. J., & Schuenemeyer, J. H. (2004). Zipf’s Law: A viable geological paradigm? Natural Resources Research, 13, 265–271.

    Article  Google Scholar 

  • Olea, R. A., Cook, T. A., & Coleman, J. L. (2010). A methodology for the assessment of unconventional (continuous) resources with an application to the Greater Natural Buttes Gas Field, Utah. Natural Resources Research, 19, 237–251.

    Article  Google Scholar 

  • Patiño- Douce, A. E. (2017). Loss distribution model for metal discovery probabilities. Natural Resources Research, 26, 241–263.

    Article  Google Scholar 

  • Schuenemeyer, J. H., & Drew, L. J. (1999). Uncovering influences on the form of oil and gas field size distributions. Natural Resources Research, 8, 37–47.

    Article  Google Scholar 

  • Sinding-Larsen, R., & Xu, J. (2005a). Bayesian analysis of the discovery process model using Markov chain Monte Carlo. Natural Resources Research, 14, 333–344.

    Article  Google Scholar 

  • Sinding-Larsen, R., & Xu, J. (2005b). Bayesian discovery process modeling of the Lower and Middle Jurassic Play of the Halten Terrace, Offshore Norway, as compared with the previous modeling. Natural Resources Research, 14, 235–248.

    Article  Google Scholar 

  • Singer, D. A. (1993). Basic concepts in three-part quantitative assessments of undiscovered mineral resources. Nonrenewable Resources, 2, 69–81.

    Article  Google Scholar 

  • Singer, D. A. (1994). Conditional estimates of the number of podiform chromite deposits. Nonrenewable Resources, 3, 200–204.

    Article  Google Scholar 

  • Singer, D. A., & Kouda, R. (2011). Probabilistic estimates of number of undiscovered deposits and their total tonnages in permissive tracts using deposit densities. Natural Resources Research, 20, 89–93.

    Article  Google Scholar 

  • Singer, D. A., & Menzie, W. D. (2008). Map scale effects on estimating the number of undiscovered mineral deposits. Natural Resources Research, 17, 79–86.

    Article  Google Scholar 

  • Xu, J., & Sinding-Larsen, R. (2005). How to choose priors for Bayesian estimation of the discovery process model. Natural Resources Research, 14, 211–233.

    Article  Google Scholar 

From NRR: Papers concerning reserve growth, peak resource, and resource depletion

  • Bartlett, A. A. (2006). A depletion protocol for non-renewable natural resources: Australia as an example. Natural Resources Research, 15, 151–164.

    Article  Google Scholar 

  • Cavallo, A. J. (2002). Predicting the peak in world oil production. Natural Resources Research, 11, 187–195.

    Article  Google Scholar 

  • Cavallo, A. J. (2004a). Hubbert’s petroleum production model: An evaluation and implications for world oil production forecasts. Natural Resources Research, 13, 211–221.

    Article  Google Scholar 

  • Cavallo, A. J. (2004b). Spare capacity (2003) and peak production in world oil. Natural Resources Research, 13, 53–56.

    Article  Google Scholar 

  • Chapman, D. (1993). World oil: Hotelling depletion or accelerating use? Nonrenewable Resources, 2, 331–339.

    Article  Google Scholar 

  • Duncan, R. C., & Youngquist, W. (1999). Encircling the peak of world oil production. Natural Resources Research, 8, 219–232.

    Article  Google Scholar 

  • Feygin, M., & Satkin, R. (2004). The oil reserves-to-production ratio and its proper interpretation. Natural Resources Research, 13, 57–60.

    Article  Google Scholar 

  • Harris, D., Miao, Y. H., Pan, G., & Wilson, T. (1992). Estimation of the potential supply of US oil by life cycle and learning models. Nonrenewable Resources, 1, 239–252.

    Article  Google Scholar 

  • Harris, D. P., & Wilson, T. (1992). Econometric and learning curve estimation of US potential oil supply. Nonrenewable Resources, 1, 323–347.

    Article  Google Scholar 

  • Höök, M., & Aleklett, K. (2010). Trends in US recoverable coal supply estimates and future production outlooks. Natural Resources Research, 19, 189–208.

    Article  Google Scholar 

  • Klett, T. R. (2005). United States Geological Survey’s reserve-growth models and their implementation. Natural Resources Research, 14, 249–264.

    Article  Google Scholar 

  • Lin, C. Y. C., Meng, H., Ngai, T. Y., Oscherov, V., & Zhu, Y. H. (2009). Hotelling revisited: Oil prices and endogenous technological progress. Natural Resources Research, 18, 29–38.

    Article  Google Scholar 

  • Matsumoto, K. I., & Voudouris, V. (2015). Potential impact of unconventional oil resources on major oil-producing countries: Scenario analysis with the ACEGES model. Natural Resources Research, 24, 107–119.

    Article  Google Scholar 

  • May, D., Prior, T., Cordell, D., & Giurco, D. (2012). Peak minerals: theoretical foundations and practical application. Natural Resources Research, 21, 43–60.

    Article  Google Scholar 

  • Mohr, S. H., & Evans, G. M. (2008). Peak oil: Testing Hubbert’s curve via theoretical modeling. Natural Resources Research, 17, 1–11.

    Article  Google Scholar 

  • Mohr, S., Giurco, D., Yellishetty, M., Ward, J., & Mudd, G. (2015). Projection of iron ore production. Natural Resources Research, 24, 317–327.

    Article  Google Scholar 

  • Nishiyama, T., & Adachi, T. (1995). Resource depletion calculated by the ratio of the reserve plus cumulative consumption to the crustal abundance for gold. Nonrenewable Resources, 4, 253–261.

    Article  Google Scholar 

  • Othman, J., & Jafari, Y. (2012). Accounting for depletion of oil and gas resources in Malaysia. Natural Resources Research, 21, 483–494.

    Article  Google Scholar 

  • Patiño- Douce, A. E. (2016). Metallic mineral resources in the twenty-first century: II. Constraints on future supply. Natural Resources Research, 25, 97–124.

    Article  Google Scholar 

  • Santini, D. J. (1998). An assessment of oil supply and its implications for future prices. Nonrenewable Resources, 7, 101–121.

    Article  Google Scholar 

  • Schmoker, J. W., & Crovelli, R. A. (1998). A simplified spreadsheet program for estimating future growth of oil and gas reserves. Nonrenewable Resources, 7, 149–155.

    Article  Google Scholar 

  • Sorrell, S., & Speirs, J. (2010). Hubbert’s legacy: A review of curve-fitting methods to estimate ultimately recoverable resources. Natural Resources Research, 19, 209–230.

    Article  Google Scholar 

  • Taylor, L. D. (1998). On depletion of an exhausting natural resource. Nonrenewable Resources, 7, 225–232.

    Article  Google Scholar 

  • Traore, F., & Zebaze, C. D. (2016). Managing depleting gold revenues in Mali: An assessment of policy options. Natural Resources Research, 25, 183–195.

    Article  Google Scholar 

  • Verma, M. K. (2005). A new reserve growth model for United States oil and gas fields. Natural Resources Research, 14, 77–89.

    Article  Google Scholar 

  • Verma, M. K., & Ulmishek, G. F. (2003). Reserve growth in oil fields of West Siberian Basin, Russia. Natural Resources Research, 12, 105–119.

    Article  Google Scholar 

  • Wachtmeister, H., Lund, L., Aleklett, K., & Höök, M. (2017). Production decline curves of tight oil wells in Eagle Ford Shale. Natural Resources Research, 26, 365–377.

    Article  Google Scholar 

From NRR: Papers concerning sustainability

  • Alazard, N., & Montadert, L. (1993). Oil resources for the next century: What’s ahead? Nonrenewable Resources, 2, 197–206.

    Article  Google Scholar 

  • Attanasi, E. D. (1998). Coal resources, new air quality standards, and sustainability. Nonrenewable Resources, 7, 271–279.

    Article  Google Scholar 

  • Attanasi, E. D., & Freeman, P. A. (2014). Commercial possibilities for stranded conventional gas from Alaska’s North Slope. Natural Resources Research, 23, 175–193.

    Article  Google Scholar 

  • Attanasi, E. D., & Schuenemeyer, J. H. (2002). Some aspects of resource uncertainty and their economic consequences in assessment of the 1002 area of the Arctic National Wildlife Refuge. Natural Resources Research, 11, 109–120.

    Article  Google Scholar 

  • Blacutt, W. P. (1995). The investment-worth model: Concepts and methods for estimation of model parameters. Nonrenewable Resources, 4, 262–272.

    Article  Google Scholar 

  • Bourrelier, P. H., & de la Tour, X. B. (1993). Fossil fuels and other energy resources in the 21st century. Nonrenewable Resources, 2, 207–225.

    Article  Google Scholar 

  • Chen, G., Li, G., & Wang, Z. (1997b). Geologic risk, economic assessment, and optimal decision making of petroleum plays in the Bohaiwan Basin, northern China. Nonrenewable Resources, 6, 329–337.

    Article  Google Scholar 

  • Coleman, J. L. (1995). The American whale oil industry: A look back to the future of the American petroleum industry? Nonrenewable Resources, 4, 273–288.

    Article  Google Scholar 

  • Duval, J. S. (2003). Economic filters applied to quantitative mineral resource simulations. Natural Resources Research, 12, 121–126.

    Article  Google Scholar 

  • Fyfe, W. S., Powell, M. A., Hart, B. R., & Ratanasthien, B. (1993). A global crisis: Energy in the future. Nonrenewable Resources, 2, 187–196.

    Article  Google Scholar 

  • Höök, M., Li, J., Johansson, K., & Snowden, S. (2012). Growth rates of global energy systems and future outlooks. Natural Resources Research, 21, 23–41.

    Article  Google Scholar 

  • Hower, J. C. (1995). Uncertain and treacherous: The cannel coal industry in Kentucky. Nonrenewable Resources, 4, 310–324.

    Article  Google Scholar 

  • Jaunky, V. C. (2012). Aluminum consumption and economic growth: Evidence from rich countries. Natural Resources Research, 21, 265–278.

    Article  Google Scholar 

  • Lemons, J. F., & Berry, D. (1996). Sustainability in a materials world. Nonrenewable Resources, 5, 277–284.

    Article  Google Scholar 

  • Long, K. R. (1995). Economics of mining law. Nonrenewable Resources, 4, 74–83.

    Article  Google Scholar 

  • MacKenzie, J. J. (1998). Oil as a finite resource. Nonrenewable Resources, 7, 97–100.

    Article  Google Scholar 

  • Majorowicz, J., & Grasby, S. E. (2014). Geothermal energy for northern Canada: Is it economical? Natural Resources Research, 23, 159–173.

    Article  Google Scholar 

  • Nappi, C., & Poulin, R. (1998). Sustainable development and mine management. Nonrenewable Resources, 7, 263–269.

    Article  Google Scholar 

  • Pimentel, D. (2003). Ethanol fuels: Energy balance, economics, and environmental impacts are negative. Natural Resources Research, 12, 127–134.

    Article  Google Scholar 

  • Roberts, M. C. (1994). Business cycles and forecasts of industrial minerals use. Nonrenewable Resources, 3, 315–324.

    Article  Google Scholar 

  • Rogich, D. G. (1996). Material use, economic growth, and the environment. Nonrenewable Resources, 5, 197–210.

    Article  Google Scholar 

  • Shields, D. J. (1998). Nonrenewable resources in economic, social, and environmental sustainability. Nonrenewable Resources, 7, 251–261.

    Article  Google Scholar 

Papers in this special issue

Papers from other sources

  • Adelman, M. A. (1990). Mineral depletion, with special reference to petroleum. The Review of Economics and Statistics, 72, 1–10.

    Article  Google Scholar 

  • Arrington, J. R. (1960). Size of crude reserve is key to evaluating exploration programs. Oil & Gas Journal, 58, 130–134.

    Google Scholar 

  • Carranza, E. J. M. (2011). From predictive mapping of mineral prospectivity to quantitative estimation of number of undiscovered prospects. Resource Geology, 61, 30–51.

    Article  Google Scholar 

  • Carranza, E. J. M., Owusu, E., & Hale, M. (2009). Mapping of prospectivity and estimation of number of undiscovered prospects for lode-gold, southwestern Ashanti Belt, Ghana. Mineralium Deposita, 44, 915–938.

    Article  Google Scholar 

  • Carranza, E. J. M., & Sadeghi, M. (2010). Predictive mapping of prospectivity and quantitative estimation of undiscovered VMS deposits in Skellefte district (Sweden). Ore Geology Reviews, 38, 219–241.

    Article  Google Scholar 

  • Cunningham, C. G., Singer, D. A., Zappettini, E. O., Vivallo, W., Celada, C. M., Quispe, J., et al. (2007). A preliminary quantitative mineral resource assessment of undiscovered porphyry copper resources in the Andes Mountains of South America. SEG Newsletter, 71, 8–13.

    Google Scholar 

  • Höök, M., & Aleklett, K. (2009). Historical trends in American coal production and a possible future outlook. International Journal of Coal Geology, 78, 201–216.

    Article  Google Scholar 

  • Hotelling, H. (1931). The economics of exhaustible resources. The Journal of Political Economy, 39, 137–175.

    Article  Google Scholar 

  • Hubbert, M. K. (1956). Nuclear energy and the fossil fuels. Shell Development Company, Exploration and Production Research Division, Houston, TX, Publication No. 95. http://www.energybulletin.net/node/13630.

  • Lambert, I., Durrheim, R., Godoy, M., Kota, M., Leahy, P., Ludden, J., et al. (2013). Resourcing future generations: a proposed new IUGS initiative. Episodes, 36(2), 82–86.

    Google Scholar 

  • Lisitsin, V. (2010). Methods of three-part quantitative assessments of undiscovered mineral resources: examples from Victoria, Australia. Mathematical Geosciences, 42, 571–582.

    Article  Google Scholar 

  • Nickless, E., Bloodworth, A., Meinert, L., Giurco, D., Mohr, S., & Littleboy, A. (2014). Resourcing future generations white paper: Mineral resources and future supply. International Union of Geological Sciences. https://www.americangeosciences.org/sites/default/files/ConsultationPaper2014_Oct_12_AL_EN_DGFINAL.PDF.

  • Rasilainen, K., Eilu, P., Halkoaho, T., Iljina, M., & Karinen, T. (2010). Quantitative mineral resource assessment of undiscovered PGE resources in Finland. Ore Geology Reviews, 38, 270–287.

    Article  Google Scholar 

Download references

Acknowledgements

I am grateful for the contributions of all the authors, even those who withdrew their submissions and those whose papers were rejected by the reviewers. Therefore, I am also thankful to the following persons for their time and effort in reviewing the papers for this special issue: A. Allanore, G.P. Andrews-Speed, L. Castro, M.D. Cocker, J. Dewulf, R. Eggert, A. Elshkaki, A.G. Gunn, L. Erdmann, K. Hanghøj, M.L.C.M. Henckens, P. Leahy, G. Pan, A.E. Patiño-Douce, L.D. Roper, M. Roberti, D. Singer, J.E. Tilton, A. Valero and F.W. Wellmer.

Author information

Authors and Affiliations

  1. School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, South Africa

    Emmanuel John M. Carranza

  2. Economic Geology Research Centre (EGRU), James Cook University, Townsville, QLD, Australia

    Emmanuel John M. Carranza

Authors
  1. Emmanuel John M. Carranza
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emmanuel John M. Carranza.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Carranza, E.J.M. Natural Resources Research Publications on Resourcing Future Generations, and Introduction of Papers in this Special Issue. Nat Resour Res 27, 125–141 (2018). https://doi.org/10.1007/s11053-018-9369-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11053-018-9369-4

Keywords

Search

Navigation