Approaches to advance scientific understanding of macrosystems ecology

Frontiers in Ecology and the Environment

Volumn 12, Issue 1, 2014, Pages 15-23

  Levy, Ofir ^a   Ball, Becky A ^b   Bond Lamberty, Ben ^c   Cheruvelil, Kendra S ^d   Finley, Andrew O ^d   Lottig, Noah R ^e   Punyasena, Surangi W ^f   Xiao, Jingfeng ^g   Zhou, Jizhong ^h   Buckley, Lauren B ⁱ   Filstrup, Christopher T ^j   Keitt, Tim H ^k   Kellner, James R ^l   Knapp, Alan K ^m   Richardson, Andrew D ⁿ   Tcheng, David ^f   Toomey, Michael ⁿ   Vargas, Rodrigo ^o   Voordeckers, James W ^h   Wagner, Tyler ^p   Williams, John W ^e   more..

^a ARIZONA STATE UNIVERSITY   (United States)

^b ARIZONA STATE UNIVERSITY WEST   (United States)

^c PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^d MICHIGAN STATE UNIVERSITY   (United States)

^e UNIVERSITY OF WISCONSIN MADISON   (United States)

^f UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^g UNIVERSITY OF NEW HAMPSHIRE   (United States)

^h UNIVERSITY OF OKLAHOMA   (United States)

ⁱ UNIVERSITY OF NORTH CAROLINA   (United States)

^j IOWA STATE UNIVERSITY   (United States)

^k UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^l BROWN UNIVERSITY   (United States)

^m Department of Environmental and Radiological Health Sciences   (United States)

ⁿ HARVARD UNIVERSITY   (United States)

^o UNIVERSITY OF DELAWARE   (United States)

^p PENNSYLVANIA STATE UNIVERSITY   (United States)

more..

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSIMILATION; DESIGN; HIERARCHICAL SYSTEM; LONG-TERM CHANGE; MACROECOLOGY; MODEL VALIDATION; RESEARCH METHOD; STANDARDIZATION; THEMATIC MAPPING; THEORETICAL STUDY;

EID: 84894266880     PISSN: 15409295     EISSN: 15409309     Source Type: Journal    
DOI: 10.1890/130019     Document Type: Article

References (43)

1. Anand M, Gonzalez A, Guichard F, et al. 2010. Ecological systems as complex systems: challenges for an emerging science. Diversity 2: 395-410.
2. Banerjee S, Gelfand AE, Finley AO, and Sang H. 2008. Gaussian predictive process models for large spatial data sets. J Roy Stat Soc B 70: 825-48.
3. Breiman L. 2001. Random forests. Mach Learn 45: 5-32.
4. Browning DM, Duniway MC, Laliberte AS, and Rango A. 2012. Hierarchical analysis of vegetation dynamics over 71 years: soil-rainfall interactions in a Chihuahuan Desert ecosystem. Ecol Appl 22: 909-26.
5. Buckley LB, Urban MC, Angilletta MJ, et al. 2010. Can mechanism inform species' distribution models? Ecol Lett 13: 1041-54.
6. Cressie N, Calder CA, Clark JS, et al. 2009. Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. Ecol Appl 19: 553-70.
7. Evans MR, Norris KJ, and Benton TG. 2012. Predictive ecology: systems approaches introduction. Philos T Roy Soc B 367: 163-69.
8. Finley AO, Banerjee S, and McRoberts RE. 2009. Hierarchical spatial models for predicting tree species assemblages across large domains. Ann Appl Stat 3: 1052-79.
9. Golley FB (Ed). 1993. A history of the ecosystem concept in ecology. New Haven, CT: Yale University Press.
10. Goring SJ, Weathers KC, Dodds WK, et al. 2014. Improving the culture of interdisciplinary collaboration in ecology by expanding measures of success. Front Ecol Environ 12: 39-47.
11. Goulden ML, Winston GC, McMillan AMS, et al. 2006. An eddy covariance mesonet to measure the effect of forest age on land-atmosphere exchange. Global Change Biol 12: 2146-62. Hagen JB (Ed). 1992. An entangled bank: the origins of ecosystem ecology. New Brunswick, NJ: Rutgers University Press.
12. Hampton SE. 2005. Increased niche differentiation between two Conochilus species over 33 years of climate change and food web alteration. Limnol Oceanogr 50: 421-26.
13. Heffernan JB, Soranno PA, Angilletta MJ, et al. 2014. Macro-systems ecology: understanding ecological patterns and processes at continental scales. Front Ecol Environ 12: 5-14.
14. Hewitt JE, Thrush S F, Dayton PK, and Bonsdorff E. 2007. The effect of spatial and temporal heterogeneity on the design and analysis of empirical studies of scale-dependent systems. Am Nat 169: 398-408.
15. Johnstone IM and Titterington DM. 2009. Statistical challenges of high-dimensional data. Philos T Roy Soc A 367: 4237-53.
16. Justice CO, Vermote E, Townshend JRG, et al. 1998. The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research. IEEE T Geosci Remote 36: 1228-49.
17. Kearney MR, Matzelle A, and Helmuth B. 2012. Biomechanics meets the ecological niche: the importance of temporal data resolution. J Exp Biol 215: 922-33.
18. Keil P, Belmaker J, Wilson AM, et al. 2013. Downscaling of species distribution models: a hierarchical approach. Method Ecol Evol 4: 82-94.
19. Kell DB and Oliver SG. 2004. Here is the evidence, now what is the hypothesis? The complementary roles of inductive and hypothesis-driven science in the post-genomic era. Bioessays 26: 99-105.
20. Kelling S, Hochachka WM, Fink D, et al. 2009. Data-intensive science: a new paradigm for biodiversity studies. BioScience 59: 613-20.
21. Lamon EC, Carpenter SR, and Stow CA. 1998. Forecasting PCB concentrations in Lake Michigan salmonids: a dynamic linear model approach. Ecol Appl 8: 659-68.
22. Levy O, Dayan T, Kronfeld-Schor N, and Porter WP. 2012. Biophysical modeling of the temporal niche: from first principles to the evolution of activity patterns. Am Nat 179: 794-804.
23. Miao S, Carstenn S, Thomas C, et al. 2009. Integrating multiple spatial controls and temporal sampling schemes to explore short-and long-term ecosystem response to fire in an Everglades wetland. In: Miao S, Carstenn S, and Nungesser M (Eds). Real world ecology. New York, NY: Springer.
24. Michener WK and Jones MB. 2012. Ecoinformatics: supporting ecology as a data-intensive science. Trends Ecol Evol 27: 85-93.
25. Nol L, Verburg PH, Heuvelink GBM, and Molenaar K. 2008. Effect of land cover data on nitrous oxide inventory in fen meadows. J Environ Qual 37: 1209-19.
26. Peters DPC, Bestelmeyer BT, and Turner MG. 2007. Cross-scale interactions and changing pattern-process relationships: consequences for system dynamics. Ecosystems 10: 790-96.
27. Peters DPC, Groffman PM, Nadelhoffer KJ, et al. 2008. Living in an increasingly connected world: a framework for continental-scale environmental science. Front Ecol Environ 6: 229-37.
28. Pole A, West M, and Harrison J (Eds). 1994. Applied Bayesian forecasting and time series analysis. New York, NY: Chapman & Hall.
29. Potapov P, Hansen MC, Stehman SV, et al. 2008. Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss. Remote Sens Environ 112: 3708-19.
30. Qian SS, Cuffney T F, Alameddine I, et al. 2010. On the application of multilevel modeling in environmental and ecological studies. Ecology 91: 355-61.
31. Rüegg J, Gries C, Bond-Lamberty B, et al. 2014. Completing the data life cycle: using information management in macrosystems ecology research. Front Ecol Environ 12: 24-30.
32. Salazar E, Sanso B, Finley AO, et al. 2011. Comparing and blending regional climate model predictions for the American Southwest. J Agr Biol Envir S 16: 586-605.
33. Sears M W, Raskin E, and Angilletta MJ. 2011. The world is not flat: defining relevant thermal landscapes in the context of climate change. Integr Comp Biol 51: 666-75
34. Settles B (Ed). 2012. Active learning. San Rafael, CA: Morgan & Claypool.
35. Shvachko K, Hairong K, Radia S, and Chansler R. 2010. The Hadoop distributed file system. In: IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST); 3-7 May 2010; Incline Village, N V. doi:10.1109/MSST.2010. 5496972.
36. Soranno PA, Cheruvelil KS, Bissell EG, et al. 2014. Cross-scale interactions: quantifying multi-scaled cause-effect relationships in macrosystems. Front Ecol Environ 12: 65-73.
37. Taylor PD, Mackenzie SA, Thurber BG, et al. 2011. Landscape movements of migratory birds and bats reveal an expanded scale of stopover. PLoS ONE 6: e27054.
38. Vargas R, Carbone M, Reichstein M, and Baldocchi D. 2011. Frontiers and challenges in soil respiration research: from measurements to model-data integration. Biogeochemistry 102: 1-13.
39. Verburg PH, Neumann K, and Nol L. 2011. Challenges in using land use and land cover data for global change studies. Glob Change Biol 17: 974-89.
40. Wallentin G, Tappeiner U, Strobl J, and Tasser E. 2008. Understanding alpine tree line dynamics: an individual-based model. Ecol Model 218: 235-46.
41. Xiao J F, Zhuang QL, Baldocchi DD, et al. 2008. Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data. Agr Forest Meteorol 148: 1827-47.
42. Xiao J F, Chen JQ, Davis KJ, and Reichstein M. 2012. Advances in upscaling of eddy covariance measurements of carbon and water fluxes. J Geophys Res-Biogeo 117: G00J01.
43. Zhou ZH and Liu XY. 2010. On multi-class cost-sensitive learning. Comput Intell 26: 232-57.