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Meetings Science at the frontier: multimethod research to evaluate ecosystem change across multiple scales Science at the Frontier: Using multimethod research to create new knowledge and assess tools across spatial and temporal scales, an organized session at the American Geophysical Union Annual Meeting in New Orleans, Louisiana, USA, December 2017 Changes in the Earth system occur across the full spectrum of spatial and temporal scales, yet our research approaches to understanding and predicting those changes are typically restricted to a pre-defined window of space and time. For this reason, there is substantial power in integrating different approaches, particularly for research associated with the multifaceted nature of ecosystem responses to global change. Within a given research approach – for example, remote sensing, field experimentation, modeling – science promotes the continued advancement of tools and techniques. As technical advancements continue at an unprecedented rate, new opportunities for integrated, multi-approach research emerge, which could more effectively capture the mechanisms and patterns that drive ecosystem structure and function. A capacity to move beyond comparison and into the realm of integration shows promise for promoting significant advances in Earth system science, as evidenced by the Organized Session Science at the Frontier: Using multimethod research to create new knowledge and assess tools across spatial and temporal scales on 12 December 2017 at the Autumn meeting of the American Geophysical Union in New Orleans, Louisiana.
Upscaling and downscaling Terrestrial ecosystems around the world face multiple interacting threats from climate change, including rising temperatures, more severe and longer lasting droughts, increasing precipitation variability, and intensifying disturbance and fire regimes. Adaptation to these growing threats requires an improved, mechanistic understanding of key ecosystem processes, thus enabling accurate ecological forecasts that can be incorporated into adaptive management frameworks. Reductionist approaches to science are a foundation of mechanistic understanding of process, yet to move from understanding of individual processes and mechanisms to predictions of whole-system behavior requires addressing complex 1318 New Phytologist (2018) 218: 1318–1320 www.newphytologist.com
interactions. Often these interactions occur at scales greater than those of the mechanisms being considered, leading to a disconnect between traditional plot-scale experimental approaches and landscape-level ecosystem function. Beverly Law (Oregon State University, USA) highlighted some of the challenges of improving carbon flux estimates from cutting-edge Earth System Models (ESMs), where large numbers of parameters cannot be calibrated in isolation due to model complexity. However, assimilating timeseries of carbon flux data derived from tall eddy covariance flux towers and spatial atmospheric CO2 profiles derived from an unmanned aerial vehicle (UAV) resulted in significantly improved model predictions of forest carbon exchange for highly productive forests in the mountainous terrain of western Oregon (Schmidt et al., 2016). In a study of dryland ecosystems, Dong Yan (University of Arizona, USA) systematically evaluated the relationship between PhenoCam-derived greenness indices and gross primary productivity (GPP) measured using the eddy covariance technique across a range of spatiotemporal scales from the canopylevel to 500 m 9 500 m MODIS pixels, and from daily to monthly time-steps. Results showed that any changes in the dominant land cover types result in divergent GPP estimates, and greenness indices best captured GPP changes at monthly scales. These studies demonstrated how utilizing multi-scale techniques provides insight into the scale-dependence of key ecosystem processes and gave powerful integrated frameworks for overcoming scaling challenges.
Data–data, data–model, model–model integration The concept and methods of data–model integration or assimilation are widely gaining traction among ecosystem ecologists (Luo et al., 2011). As a field, ecology is moving past the era in which data collection and modeling proceed independently or sequentially, and increasingly, plans for data–model integration are viewed as a critical component of research design. Several talks during the Session, notably those by Scott Cory (Wake Forest University, Winston-Salem, NC, USA) and Jeffrey Stenzel (University of Idaho, USA) showcased early career scientists thoughtfully developing research approaches where modeling and field data collection were considered within a common framework. Less frequently, or perhaps less explicitly, considered are the challenges of integrating insights from different types of data or different models. Some highlights of the session emerged with insights drawn from data collected using techniques operating at vastly different scales. For instance, Abigail Swann (University of Washington, Seattle, WA, USA) used a combination of multiple rainfall data sets, Amazon river discharge estimates, and GRACE satellite estimates of Amazon water storage to estimate evapotranspiration rates across the entire Amazon basin, providing a refined understanding of water fluxes during the wet and dry seasons in seasonally dry forests (Swann & Koven, 2017). Similarly, Matthew Ó 2018 The Authors New Phytologist Ó 2018 New Phytologist Trust
New Phytologist Dannenberg (University of Arizona, USA) and Erika Wise (University of North Carolina at Chapel Hill, USA) integrated high frequency atmospheric re-analysis data, a large tree ring network, and remotely sensed vegetation greenness data to better understand the responses of key ecosystem processes – including forest growth, vegetation phenology, and wildfire activity – to variation in the positions of Pacific storm tracks across western North America. A consistent signal emerged from the data integration, which suggested that shifting Pacific storm tracks exerted strong controls on regional hydroclimate and ecosystem processes, which have profound implications given projected changes in Pacific storm track positions in the twenty-first century (Dannenberg & Wise, 2017). Only through the integration of multiple independent data sources were these efforts able to characterize signal-to-noise and thus forge new understanding in the field. In the rapidly changing Arctic and Boreal regions of the world, sparse ground level data must be complemented with remote sensing and models to capture the ongoing, rapid changes in biogeochemical cycling. Scott Goetz (Northern Arizona University, USA) presented results from the NASA-led Arctic and Boreal Vulnerability Experiment (ABoVE), where multimethod research involving large numbers of researchers across many disciplines has led to important insights about changing vegetation in the Arctic. For example, one fascinating study by Veraverbeke et al. (2017) that integrated ecosystem modeling, remote sensing, and climate data, found that increased lightning and warmer conditions at the Arctic treeline may accelerate the migration of boreal forest trees into formerly treeless Arctic tundra.
Climate–carbon–water: different frequencies, different scales, inseparably linked Multiple studies across a range of systems suggested ecosystem carbon fluxes were more tightly coupled to water variability than previously recognized. Mallory Barnes (University of Arizona, USA) presented evidence that upscaling GPP estimates from a network of 25 AmeriFlux eddy covariance towers across the southwest United States using machine learning approaches, with remotely sensed vegetation inputs, and interpolated meteorological inputs, better captured the ‘flashy’ or pulsed GPP characteristic of these systems (Barnes et al., 2016). Recent work has shown that interannual variability of CO2 exchange between wet and dry years in southwest desert ecosystems may be 3–5 times higher than previously estimated (Biederman et al., 2017), which is important in the global context where dryland ecosystems may be the dominant source of variability in the land CO2 sink (Ahlstr€om et al., 2015). The tight link between interannual and subannual water availability and carbon cycling in drylands was mirrored for a wetter system in a talk by Neil Pederson (Lamont-Doherty Earth Observatory, Palisades, NY, USA), in which results suggested that forest productivity in mesic temperate forests was determined by water availability (Levesque et al., 2017), in contrast to dynamic global vegetation models (DGVMs) in which CO2 fertilization is a stronger Ó 2018 The Authors New Phytologist Ó 2018 New Phytologist Trust
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control. In this same talk, tree-ring isotopic composition (d13C and d18O) was used to infer long-term patterns in net primary production across the region. While sophisticated chemistry and satellite-derived data contributed to these finding, Dr Pederson discussed how his work also represented science at ‘the frontier of natural history’, where detailed knowledge of a species’ biology is critical to an integrated perspective on biome-scale changes. Multi-scale research also allows for assessment of contrasting patterns of ecosystem function across biome-scale climate gradients. For instance, in his talk on grassland productivity on the Great Plains, William Parton (Colorado State University, USA) showed that the northern and southern Great Plains ecosystems demonstrated opposite patterns in production in relation to phases of El Ni~ no and the Pacific Decadal Oscillation, and these sea surface temperature anomalies have large impacts on the mean and the variability of annual production in both regions (Chen et al., 2017). Even at the scale of individual trees and small forests plots, variability in ecosystem carbon uptake may be higher than expected, as suggested by Jeffrey Stenzel, who compared Treehugger Band Dendrometers to ecosystem carbon fluxes, and found that coniferous forest carbon fixation was tightly coupled to trunk water content, which was found to be highly variable across spatiotemporal scales.
Tools for people on the land Landscape- and biome-scale changes in the structure and function of terrestrial ecosystems often have implications for how humans live on the land. Multimethod research has the potential to translate information across scales that improves its utility for land managers, policy-makers, and citizens. William Parton presented an interesting example where insights from highly complex research – integrating hands-and-knees fieldwork (clip harvesting grasses to measure growth), satellite-based remote sensing, and modeled climate that was downscaled to soil microclimate using DAYCENT– could be used to provide ranchers near-term ecological forecasts of grassland productivity (termed the ‘GrassCast’ product) to help guide stocking and herd management decisions (Chen et al., 2017). As another example, in the highly productive coastal forests of Oregon, large amounts of carbon are stored in tree biomass, and these same trees are a highly valuable source of raw material for the forestry industry. The work presented by Beverly Law suggested that timber harvests were the largest source of mortality for mature trees, beyond fire and bark beetles events (Berner et al., 2017), and suggested that managing forestry activities to maintain and enhance forest carbon stocks would require accelerated integration of data collection and ecosystem modeling at timescales relevant to management activities. Similarly, although at a much different scale, Scott Cory demonstrated that downscaling climate projections to the microclimate of the soil surface could be critical for evaluating the survival of tree seedlings at the life phase that represents the most critical filter to establishment, which could have real implications for the Christmas tree forestry economy of Appalachia (Cory et al., 2017). New Phytologist (2018) 218: 1318–1320 www.newphytologist.com
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Where do we go from here?
References
The use of multiple methods to assess complex questions is not new to science, yet increased technological advances and computing power now allow for the bridging of diverse disciplines that each bring a large amount of data to the table. As a whole, a principal theme that emerged from this session was the large knowledge benefits of integrating data and models across multiple scales and multiple disciplines, especially in an era when models can be used to integrate or assimilate satellite data and field-based measurements at a rate approaching real-time. These integrated multimethod approaches are transforming our view of the Earth system, especially with regard to linkages between water and carbon cycling, and the climate system. As our understanding is refined, the ability of an ecologist to provide meaningful near-term forecasts and long-term predictions is becoming a real tool for land managers and citizens (Bonan & Doney, 2018; Dietze et al., 2018). The multimethod approaches highlighted here do not supplant traditional ecological research, and some of the most interesting insights emerged when scientists combined their knowledge of natural history and site-specific ecology with cutting edge computational and satellite-based tools. As multimethod approaches advance, consideration of how to integrate across data sets, and between data and models, during the project design phase will prove increasingly critical.
Ahlstr€om A, Raupach MR, Schurgers G, Smith B, Arneth A, Jung M, Reichstein M, Canadell JG, Friedlingstein P, Jain AK et al. 2015. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348: 895–899. Barnes ML, Moran MS, Scott RL, Kolb TE, Ponce-Campos GE, Moore DJP, Ross MA, Mitra B, Dore S. 2016. Vegetation productivity responds to sub-annual climate conditions across semiarid biomes. Ecosphere 7: e01339. Berner LT, Law BE, Meddens AJH, Hicke JA. 2017. Tree mortality from fires, bark beetles, and timber harvest during a hot and dry decade in the western United States (2003–2012). Environmental Research Letters 12: 065005. Biederman JA, Scott RL, Bell TW, Bowling DR, Dore S, Garatuza-Payan J, Kolb TE, Krishnan P, Krofcheck DJ, Litvak ME et al. 2017. CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America. Global Change Biology 23: 4204–4221. Bonan GB, Doney SC. 2018. Climate, ecosystems, and planetary futures: the challenge to predict life in Earth system models. Science 359: eaam8328. Chen M, Parton WJ, Del Grosso SJ, Hartman MD, Day KA, Tucker CJ, Derner JD, Knapp AK, Smith WK, Ojima DS et al. 2017. The signature of sea surface temperature anomalies on the dynamics of semiarid grassland productivity. Ecosphere 8: e02069. Cory ST, Wood LK, Neufeld HS. 2017. Phenology and growth responses of Fraser fir (Abies fraseri) Christmas trees along an elevational gradient, southern Appalachian Mountains, USA. Agricultural and Forest Meteorology 243: 25–32. Dannenberg MP, Wise EK. 2017. Shifting Pacific storm tracks as stressors to ecosystems of western North America. Global Change Biology 23: 4896–4906. Dietze MC, Fox A, Beck-Johnson LM, Betancourt JL, Hooten MB, Jarnevich CS, Keitt TH, Kenney MA, Laney CM, Larsen LG et al. 2018. Iterative near-term ecological forecasting: needs, opportunities, and challenges. Proceedings of the National Academy of Sciences, USA 115: 1424–1432. Levesque M, Andreu-Hayles L, Pederson N. 2017. Water availability drives gas exchange and growth of trees in northeastern US, not elevated CO2 and reduced acid deposition. Scientific Reports 7: 46158. Luo Y, Ogle K, Tucker C, Fei S, Gao C, LaDeau S, Clark JS, Schimel DS. 2011. Ecological forecasting and data assimilation in a data-rich era. Ecological Applications 21: 1429–1442. Schmidt A, Law BE, G€ockede M, Hanson C, Yang Z, Conley S. 2016. Bayesian optimization of the community land model simulated biosphere–atmosphere exchange using CO2 observations from a dense tower network and aircraft campaigns over Oregon. Earth Interactions 20: 1–35. Swann ALS, Koven CD. 2017. A direct estimate of the seasonal cycle of evapotranspiration over the Amazon basin. Journal of Hydrometeorology 18: 2173–2185. Veraverbeke S, Rogers BM, Goulden ML, Jandt RR, Miller CE, Wiggins EB, Randerson JT. 2017. Lightning as a major driver of recent large fire years in North American boreal forests. Nature Climate Change 7: 529.
Acknowledgements The authors offer their sincerest thanks to all the presenters that contributed to the organized oral and poster session. The authors are also grateful to Stan Wullschleger for ideas that added greatly to this session. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Colin Tucker1*, Dong Yan2, Matthew Dannenberg2, Sasha C. Reed1 and William Smith2 1
Southwest Biological Science Center, US Geological Survey, Moab, UT 84532, USA; 2 School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA (*Author for correspondence: tel +1 435 719 2337; email
[email protected])
New Phytologist (2018) 218: 1318–1320 www.newphytologist.com
Key words: biogeochemistry, emerging tools, empirical science, global change ecology, modeling, plant sciences, remote sensing.
Ó 2018 The Authors New Phytologist Ó 2018 New Phytologist Trust
