Hydroclimatological data and analyses from a headwaters region of Mongolia as boundary objects in interdisciplinary climate change research

N.B.H. VENABLE

PDF(3402 KB)
PDF(3402 KB)
Front. Earth Sci. ›› 2017, Vol. 11 ›› Issue (3) : 457-468. DOI: 10.1007/s11707-017-0644-1
RESEARCH ARTICLE
RESEARCH ARTICLE

Hydroclimatological data and analyses from a headwaters region of Mongolia as boundary objects in interdisciplinary climate change research

Author information +
History +

Abstract

Collaborative work on increasingly complex hydroclimatic investigations often crosses disciplinary boundaries. Elements of scientific inquiry, such as data or the results of analyses can become objectified, or capable of being adopted and/or adapted by users from multiple disciplinary realms. These objects often provide a bridge for collaborative endeavors, or are used as tools by individuals pursuing multi-disciplinary work. Boundary object terminology was first formalized and applied by social scientists. However, few examples of the application of this useful framework are found in the hydrologic literature. The construct is applied here to identify and discuss how common research products and processes are used both internally and externally through providing examples from a project examining the historical and paleo proxy-based hydroclimatology of a headwaters region of Mongolia. The boundary object concept is valuable to consider when conducting and critiquing basic research, collaborating across multiple disciplinary teams as when studying climate change issues, as an individual researcher working in a cross boundary sense using methods from differing disciplines to answer questions, and/or when one group adapts the work of another to their own research problems or interpretive needs, as occurred with selected products of this project.

Keywords

Mongolia / boundary objects / climate change / hydroclimate

Cite this article

Download citation ▾
N.B.H. VENABLE. Hydroclimatological data and analyses from a headwaters region of Mongolia as boundary objects in interdisciplinary climate change research. Front. Earth Sci., 2017, 11(3): 457‒468 https://doi.org/10.1007/s11707-017-0644-1
Author’s Biography

Dr. Niah B. H. Venable is a hydrologist and earth science educator with a BS in Forestry, Geology minor, Oklahoma State University, Stillwater, OK, USA, 1997, a MS Earth Science, Hydrogeology specialization, Western Michigan University, Kalamazoo, MI, USA, 2006, and a PhD Earth Sciences, Watershed Science program, Colorado State University, Fort Collins, CO, USA, 2016.

She has worked in natural resources management, industry, and academics, and has been employed as an instructor for both the Geosciences and Ecosystem Science and Sustainability Departments at Colorado State University. She is currently a postdoctoral researcher with the Colorado State Forest Service in Fort Collins, CO, and is interested in natural resources management and climate change affects on hydrology.

Dr. Venable has participated in the American Geophysical Union, the Tree-ring Society, and the American Center for Mongolian Studies professional organizations, and has been awarded the Anderson Graduate Fellowship, the Dils Watershed Science Scholarship, the Information and Technology Center PhD Scholar Award, and the National Science Foundation Alliances for Graduate Education and the Professoriate Fellowship while at Colorado State University. She can be reached by email at: niah.venable@gmail.com.

References

[1]
Akkerman S F, Bakker A (2011). Boundary crossing and boundary objects. Rev Educ Res, 81(2): 132–169
CrossRef Google scholar
[2]
Beaulieu C, Ouarda T, Seidou O (2007). A review of homogenization techniques for climate data and their applicability to precipitation series. Hydrological Sciences Journal-Journal des Sciences Hydrologiques, 52: 18–37
CrossRef Google scholar
[3]
Becker A, Finger P, Meyer-Christoffer A, Rudolf B, Schamm K, Schneider U, Ziese M (2013). A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present. Earth Syst Sci Data, 5(1): 71–99
CrossRef Google scholar
[4]
Blades J J, Klos P Z, Kemp K B, Hall T E, Force J E, Morgan P, Tinkham W T (2016). Forest managers’ response to climate change science: evaluating the constructs of boundary objects and organizations. For Ecol Manage, 360: 376–387
CrossRef Google scholar
[5]
Bruegger R A, Jigjsuren O, Fernandez-Gimenez M E (2014). Herder observations of rangeland change in Mongolia: indicators, causes, and application to community-based management. Rangeland Ecol Manag, 67(2): 119–131
CrossRef Google scholar
[6]
Davi N K, Pederson N, Leland C, Nachin B, Suran B, Jacoby G C (2013). Is eastern Mongolia drying? A long-term perspective of a multidecadal trend. Water Resour Res, 49(1): 151–158
CrossRef Google scholar
[7]
Easterling D R, Peterson T C, Karl T R (1996). On the development and use of homogenized climate datasets. J Clim, 9(6): 1429–1434
CrossRef Google scholar
[8]
Ensor L A, Robeson S M (2008). Statistical characteristics of daily precipitation: comparisons of gridded and point datasets. J Appl Meteorol Climatol, 47(9): 2468–2476
CrossRef Google scholar
[9]
Fassnacht S R, Sukh T, Fernandez-Gimenez M E, Batbuyan B, Venable N B H, Laituri M, Adyabadam G (2011). Local understanding of hydro-climatic changes in Mongolia. In: Proceedings of H02 Symposium Cold Region Hydrology in a Changing Climate. IAHS Publication, 346: 120–129
[10]
Fernandez-Gimenez M (1993). The role of ecological perception in indigenous resource management: a case study from the Mongolian forest-steppe. Nomad People, 33: 31–46
[11]
Fernandez-Gimenez M E (2000). The role of Mongolian nomadic pastoralists’ ecological knowledge in rangeland management. Ecol Appl, 10(5): 1318–1326
CrossRef Google scholar
[12]
Fernandez-Gimenez M E, Angerer J P, Allegretti A M, Fassnacht S R, Byamba A, Chantsallkham J, Reid R S, Venable N B H (2015b). Integrating herder observations, meteorological data and remote sensing to understand climate change patterns and impacts across an eco-climatic gradient in Mongolia. In: Fernandez-Gimenez M E, Batkhishig B, Fassnacht S R, Wilson D, eds. Proceedings of Building Resilience of Mongolia’s Rangelands: A Transdisciplinary Conference. Nutag Action and Research Institute, Ulaanbaatar, Mongolia, 228–234
[13]
Fernandez-Gimenez M E, Batbuyan B (2004). Law and disorder: local implementation of Mongolia’s Land Law. Dev Change, 35(1): 141–166
CrossRef Google scholar
[14]
Fernandez-Gimenez M E, Batkhishig B, Batbuyan B (2012). Cross-boundary and cross- level dynamics increase vulnerability to severe winter disasters (dzud) in Mongolia. Glob Environ Change, 22(4): 836–851
CrossRef Google scholar
[15]
Fernandez-Gimenez M E, Batkhishig B, Batbuyan B, Ulambayar T (2015a). Lessons from the dzud: community-based rangeland management increases the adaptive capacity of Mongolian herders to winter disasters. World Dev, 68: 48–65
CrossRef Google scholar
[16]
Fritts H C (2001). Tree Rings and Climate. Caldwell: Blackburn Press, 1–567
[17]
Gilbert R O (1987). Statistical Methods for Environmental Pollution Monitoring. New York: John Wiley & Sons, 1–320
[18]
Green D, Raygorodetsky G (2010). Indigenous knowledge of a changing climate. Clim Change, 100(2): 239–242
CrossRef Google scholar
[19]
Harris I, Jones P D, Osborn T J, Lister D H (2014). Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset. Int J Climatol, 34(3): 623–642
CrossRef Google scholar
[20]
Helsel D R, Hirsch R M (2002). Statistical methods in water resources. In: Techniques of Water-Resources Investigations of the United States Geological Survey, Book 4, Hydrologic Analysis and Interpretation, Chapter A3. http://water.usgs.gov/pubs/twri/twri4a3/. Accessed 2014-11-02
[21]
Jigjisuren O, Baival B, Nayanaa K, Jargalsaikhan A, Dash K, Badamkhand B, Bud A (2015). Evaluating the impact of climate change based on herder’s observations and comparing it with hydroclimatic and remote sensing data. In: Fernandez- Gimenez M E, Batkhishig B, Fassnacht S R, and Wilson D, eds. Proceedings of Building Resilience of Mongolia’s Rangelands: A Transdisciplinary Conference held June 9–10, 2015. Nutag Action and Research Institute, Ulaanbaatar, Mongolia, 235–243
[22]
Kendall M G, Gibbons J D (1990). Rank Correlation Methods (5th ed).London: Edward Arnold, Hodder and Stoughton
[23]
Kimble C, Grenier C, Goglio-Primard K (2010). Innovation and knowledge sharing across professional boundaries: political interplay between boundary objects and brokers. Int J Inf Manage, 30(5): 437–444
CrossRef Google scholar
[24]
Klein J T (1996). Crossing Boundaries: Knowledge, Disciplinarities, and Interdisciplinarities. University of Virginia Press, 300 pp
[25]
Laituri M J, Linn S, Fassnacht S R, Venable N B H, Jamiyansharav K, Ulambayar T, Allegretti A M, Reid R S, Fernandez-Gimenez M E (2015). The MOR2 Database: building integrated datasets for social-ecological analysis across cultures and disciplines. In: Fernandez-Gimenez M E, Batkhishig B, Fassnacht S R, Wilson D, eds. Proceedings of Building Resilience of Mongolia’s Rangelands: A Transdisciplinary Conference held June 9–10, 2015. Nutag Action and Research Institute, Ulaanbaatar, Mongolia, 209–215
[26]
Leland C, Pederson N, Hessl A, Nachin B, Davi N, D’Arrigo R, Jacoby G (2013). A hydroclimatic regionalization of central Mongolia as inferred from tree rings. Dendrochronologia, 31(3): 205–215
CrossRef Google scholar
[27]
Lkhagvadorj D, Hauck M, Dulamsuren C H, Tsogtbaatar J (2013). Pastoral nomadism in the forest-steppe of the Mongolian Altai under a changing economy and warming climate. J Arid Environ, 88: 82–89
CrossRef Google scholar
[28]
Loaiciga H A, Haston L, Michaelsen J (1993). Dendrohydrology and long-term hydrologic phenomena. Rev Geophys, 31(2): 151–171
CrossRef Google scholar
[29]
Lynch A H, Tryhorn L, Abramson R (2008). Working at the boundary- Facilitating interdisciplinarity in climate change adaptation research. Bull Am Meteorol Soc, 89(2): 169–179
CrossRef Google scholar
[30]
Mann H B (1945). Nonparametric tests against trend. Econometrica, 13(3): 245–259
CrossRef Google scholar
[31]
Marin A (2010). Riders under storms: contributions of nomadic herder’s observations to analyzing climate change in Mongolia. Glob Environ Change, 20(1): 162–176
CrossRef Google scholar
[32]
McGreavy B, Hutchins K, Smith H, Lindenfeld L, Silka L (2013). Addressing the complexities of boundary work in sustainability science through communication. Sustainability, 5(10): 4195–4221
CrossRef Google scholar
[33]
Meko D M, Woodhouse C A (2007). Chapter 8: Application of streamflow reconstruction to water resources management. In: Hughes M K, Swetnam T W, Diaz H F, eds. Dendroclimatology. Developments in Paleoenvironmental Research Volume 11, New York: Springer, 231–261,
CrossRef Google scholar
[34]
Mitchell T D, Jones P D (2005). An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol, 25(6): 693–712
CrossRef Google scholar
[35]
National Statistical Office of Mongolia (2015). Mongolia Livestock Statistical Data. National Statistical Office of Mongolia, Ulaanbaatar, Mongolia
[36]
Parker J, Crona B (2012). On being all things to all people: boundary organizations and the contemporary research university. Soc Stud Sci, 42(2): 262–289
CrossRef Google scholar
[37]
Pederson N, Leland C, Nachin B, Hessl A E, Bell A R, Martin-Benito D, Saladyga T, Suran B, Brown P M, Davi N K (2013). Three centuries of shifting hydroclimatic regimes across the Mongolian Breadbasket. Agric Meteorol, 178: 10–20
CrossRef Google scholar
[38]
Regdel D, Dugarzhav C, Gunin P D (2012). Ecological demands on socioeconomic development of Mongolia under climate aridization. Arid Ecosystems, 2(1): 1–10
CrossRef Google scholar
[39]
Rhoten D, Parker A (2004). Education: risks and rewards of an interdisciplinary research path. Science, 306(5704): 2046
CrossRef Google scholar
[40]
Rockstrom J, Steffen W, Noone K, Persson A, Chapin F S III, Lambin E F, Lenton T M, Scheffer M, Folke C, Schellnhuber H J, Nykvist B, de Wit C A, Hughes T, van der Leeuw S, Rodhe H, Sorlen S, Snyder P K, Costanza R, Svedin U, Falkenmark M, Karlberg L, Corell R W, Fabry V J, Hansen J, Walker B, Liverman D, Richardson K, Crutzen P, Foley J A (2009). A safe operating space for humanity. Nature, 461(7263): 472–475
CrossRef Google scholar
[41]
Sen P K (1968). Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc, 63(324): 1379–1389
CrossRef Google scholar
[42]
Star S L (2010). This is not a boundary object: reflections on the origin of a concept. Sci Technol Human Values, 35(5): 601–617
CrossRef Google scholar
[43]
Star S L, Griesemer J R (1989). Institutional ecology, “translations” and boundary objects: amateurs and professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39. Soc Stud Sci, 19(3): 387–420
CrossRef Google scholar
[44]
Sternlieb F, Bixler R P, Huber-Stearns H, Huayhuaca C (2013). A question of fit: reflections on boundaries, organizations, and social-ecological systems. J Environ Manage, 130: 117–125
CrossRef Google scholar
[45]
Stockton C W (1971). The feasibility of augmenting hydrologic records using tree-ring data. Unpublished PhD Dissertation for PhD degree. The University of Arizona, Tucson, AZ, USA, 185 pp
[46]
Sukh T (2012). Local understanding of hydro-climate changes in Mongolia. Unpublished MS Thesis, Colorado State University, Fort Collins, Colorado, USA
[47]
Sundberg M (2007). Parameterizations as boundary objects on the climate arena. Soc Stud Sci, 37(3): 473–488
CrossRef Google scholar
[48]
Thiel H (1950). A rank-invariant method of linear and polynomial regression analysis, I, II, III. In: Proceedings of the Royal Netherlands Academy of Sciences 53, 386–392, 521–525, 1397–1412
[49]
van Pelt S C, Haasnoot M, Arts B, Ludwig F, Swart R, Biesbroek R (2015). Communicating climate (change) uncertainties: simulation games as boundary objects. Environ Sci Policy, 45: 41–52
CrossRef Google scholar
[50]
Venable N B H (2016). Trends and Tree-Rings: An Investigation of the Historical and Paleo Proxy Hydroclimate Record of the Khangai Mountain Region of Mongolia. Unpublished PhD Dissertation, Colorado State University, Fort Collins, Colorado, USA
[51]
Venable N B H, Fassnacht S R (2013). Reconstructing a water balance for North Crestone Creek: streamflow variability and extremes in a snowmelt-dominated internal drainage basin. Colorado Water: Newsletter of the Water Center of Colorado State University, 30(5): 10–14
[52]
Venable N B H, Fassnacht S R (2015). Climate change assessment issues and implications for hydro-ecology in Mongolia. In: Building Resilience of Mongolia's Rangelands: A Transdisciplinary Conference, Ulaanbataar, Mongolia, June 9, 2015
[53]
Venable N B H, Fassnacht S R, Adyabadam G (2014). To grid or not to grid… Precipitation data and hydrological modeling in the Khangai Mountain region of Mongolia. 2014 American Geophysical Union Fall Meeting, San Francisco, CA, December15–19, 2014
[54]
Venable N B H, Fassnacht S R, Adyabadam G, Tumenjargal S, Fernandez-Gimenez M, Batbuyan B (2012). Does the length of station record influence the warming trend that is perceived by Mongolian herders near the Khangai Mountains? Pirineos, 167(0): 69–86
CrossRef Google scholar
[55]
Venable N B H, Fassnacht S R, Hendricks A S (2015). Spatial changes in climate across Mongolia. In: Fernandez-Gimenez M E, Batkhishig B, Fassnacht S R, Wilson D, eds. Proceedings of Building Resilience of Mongolia’s Rangelands: A Transdisciplinary Conference held June 9–10, 2015. Nutag Action and Research Institute, Ulaanbaatar, Mongolia, 73–77
[56]
Whetton P, Hennessy K, Clarke J, McInnes K, Kent D (2012). Use of representative climate futures in impact and adaptation assessment. Clim Change, 115(3–4): 433–442
CrossRef Google scholar
[57]
Willmott C J, Robeson S M (1995). Climatologically aided interpolation (CAI) of terrestrial air temperature. Int J Climatol, 15(2): 221–229
CrossRef Google scholar
[58]
Willmott C J, Rowe C M, Philpot W D (1985). Small-scale climate maps: a sensitivity analysis of some common assumptions associated with grid-point interpolation and contouring. Am Cartogr, 12(1): 5–16
CrossRef Google scholar
[59]
Wolf J M, Venable N B H (2015). Earlywood, latewood, and adjusted latewood correlations to precipitation: a test case from the Khangai Mountains of Mongolia. In: Fernandez-Gimenez M E, Batkhishig B, Fassnacht S R, Wilson D, eds Proceedings of Building Resilience of Mongolia's Rangelands: A Transdisciplinary Conference held June 9–10, 2015. Nutag Action and Research Institute, Ulaanbaatar, Mongolia, 87–93
[60]
Wyborn C (2015). Connectivity conservation: boundary objects, science narratives and the co-production of science and practice. Environ Sci Policy, 51: 292–303
CrossRef Google scholar
[61]
Yu F, Price K P, Ellis J, Shi P (2003). Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sens Environ, 87(1): 42–54
CrossRef Google scholar
[62]
Zalasiewicz J, Williams M, Haywood A, Ellis M (2011). The Anthropocene: a new epoch of geological time? Philosophical Transactions of the Royal Society of London A: Mathematical, 369: 835–841
CrossRef Google scholar

Acknowledgements

The author would like to thank Dr. Gelegpil Adyabadam and her colleagues from the Mongolian Research and Information Institute of Meteorology, Hydrology, and Environment for providing access to the Mongolian hydroclimate data used in the original analyses. Thanks are also extended to four anonymous reviewers and the associate editor, whose comments and suggestions facilitated substantial improvements to this document. Partial support for this research was provided by the National Science Foundation Dynamics of Coupled Natural and Human Systems Program (Award BCS-1011801 entitled Does Community-Based Rangeland Ecosystem Management Increase Coupled Systems' Resilience to Climate Change in Mongolia?, PI Dr. Maria Fernandez-Gimenez) and by the American Center for Mongolian Studies US-Mongolia Field Research Fellowship Program.

RIGHTS & PERMISSIONS

2017 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(3402 KB)

Accesses

Citations

Detail

Sections
Recommended

/