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Thermal acclimation of ecosystem processes to climate warming

NEW PHYTOLOGIST 2025年第2期245卷 437-439页

作者： Wang, Jinsong Niu, Shuli Chinese Acad Sci Key Lab Ecosyst Network Observat & Modeling Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China Univ Chinese Acad Sci Dept Ecol Beijing 100049 Peoples R China Univ Chinese Acad Sci Dept Environm Beijing 100049 Peoples R China

This article is a Commentary on Lu et al . (2025), 245 : 523–533 .

关键词： adaptation data-model integration ecosystem processes plant phenology thermal acclimation whole-ecosystem warming

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Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model

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GLOBAL CHANGE BIOLOGY 2022年第2期28卷 665-684页

作者： Kyker-Snowman, Emily Lombardozzi, Danica L. Bonan, Gordon B. Cheng, Susan J. Dukes, Jeffrey S. Frey, Serita D. Jacobs, Elin M. McNellis, Risa Rady, Joshua M. Smith, Nicholas G. Thomas, R. Quinn Wieder, William W. Grandy, A. Stuart Univ New Hampshire Dept Nat Resources & Environm Durham NH 03824 USA Natl Ctr Atmospher Res Climate & Global Dynam Lab POB 3000 Boulder CO 80307 USA Univ Michigan Dept Ecol & Evolutionary Biol Ann Arbor MI 48109 USA Univ Michigan Ctr Res Learning & Teaching Ann Arbor MI 48109 USA Purdue Univ Dept Forestry & Nat Resources W Lafayette IN 47907 USA Purdue Univ Dept Biol Sci W Lafayette IN 47907 USA Texas Tech Univ Dept Biol Sci Lubbock TX 79409 USA Virginia Tech Dept Forest Resources & Environm Conservat Blacksburg VA USA Univ Colorado Inst Arctic & Alpine Res Boulder CO 80309 USA

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change, and broadening the impact of ecological research.

关键词： collaborative bridging data-model integration Earth system models global ecology history of models interdisciplinary workflow modeling across scales

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A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity

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AGRICULTURAL AND FOREST METEOROLOGY 2019年 274卷 184-194页

作者： Liu, Shaoqing Ng, Gene-Hua Crystal Univ Minnesota Twin Cities Dept Earth Sci Minneapolis MN 55455 USA Univ Minnesota Twin Cities St Anthony Falls Lab Minneapolis MN USA

Recent studies have begun to incorporate spatially variable plant traits into ecohydrological models, but temporal trait variability remains under-studied. Because of its potential to influence ecosystem function, representing stress-induced temporal trait variability into models should be a research priority. We present a new data-model integration approach to identify temporal variability in plant traits and generate stochastic-in-time model parameterizations. The data-conditioned stochastic parameterization was developed within the CLM 4.5 model utilizing global trait data as prior information and tested for a desert shrubland site. A synthetic experiment demonstrated that the framework successfully uncovered time-varying trait values. Using in-situ ecohydrological observations, we found the specific leaf area (SLA) for a common broadleaf-evergreen-shrub to be temporally dynamic and significantly correlated with seasonal water availability. We constructed a regression model based on the data-conditioned SLA estimates and soil wetness and used it to generate stochastic SLA parameters for a 40-year hindcast simulation. The stochastic-in-time SLA parameters resulted in greater productivity and water use efficiency than a standard static parameter. Our stochastic-in-time method can help evaluate stress-induced trait plasticity that extends our understanding beyond sparse spatial plant trait database and improve our ability to simulate carbon and water fluxes under global change.

关键词： Plant trait data-model integration Ecohydrological models Stochastic parameterization Temporal trait variability

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Reduced carbon use efficiency and increased microbial turnover with soil warming

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GLOBAL CHANGE BIOLOGY 2019年第3期25卷 900-910页

作者： Li, Jianwei Wang, Gangsheng Mayes, Melanie A. Allison, Steven D. Frey, Serita D. Shi, Zheng Hu, Xiao-Ming Luo, Yiqi Melillo, Jerry M. Tennessee State Univ Dept Agr & Environm Sci Nashville TN 37203 USA Oak Ridge Natl Lab Environm Sci Div Climate Change Sci Inst Oak Ridge TN USA Univ Oklahoma Dept Microbiol & Plant Biol Inst Environm Genom Norman OK 73019 USA Univ Calif Irvine Dept Ecol & Evolutionary Biol Irvine CA 92717 USA Univ Calif Irvine Dept Earth Syst Sci Irvine CA USA Univ New Hampshire Dept Nat Resources & Environm Durham NH 03824 USA Univ Oklahoma Sch Meteorol Ctr Anal & Predict Storms Norman OK 73019 USA No Arizona Univ Dept Biol Sci Ctr Ecosyst Sci & Soc Box 5640 Flagstaff AZ 86011 USA Marine Biol Lab Ctr Ecosyst Woods Hole MA 02543 USA

Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of <1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming.

关键词： carbon use efficiency (CUE) data-model integration Harvard forest microbial biomass turnover (rB) soil warming temperature sensitivity

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Dating, synthesis, and interpretation of palaeoclimatic records of the Last Glacial cycle and model-data integration: advances by the INTIMATE (integration of Ice-core, MArine and TErrestrial records) COST Action ES0907 Introduction

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QUATERNARY SCIENCE REVIEWS 2014年 106卷 1-13页

作者： Rasmussen, Sune O. Birks, Hilary H. Blockley, Simon P. E. Brauer, Achim Hajdas, Irka Hoek, Wim Z. Lowe, J. John Moreno, Ana Renssen, Hans Roche, Didier M. Svensson, Anders M. Valdes, Paul Walker, Mike J. C. Univ Copenhagen Niels Bohr Inst Ctr Ice & Climate Juliane Maries Vej 30 DK-2100 Copenhagen Denmark Univ Bergen Dept Biol N-5020 Bergen Norway Univ Bergen Bjerknes Ctr Climate Res N-5020 Bergen Norway Univ London Quaternary Res Ctr Egham TW20 0EX Surrey England GFZ German Res Ctr Geosci Sect Climate Dynam & Landscape Evolut 5 2 D-14473 Potsdam Germany ETH Lab Ion Beam Phys CH-8093 Zurich Switzerland Univ Utrecht Fac Geosci Dept Phys Geog NL-3508 TC Utrecht Netherlands CSIC Dept Geoenvironm Proc & Global Change Pyrenean Inst Ecol Zaragoza 50059 Spain Vrije Univ Amsterdam Fac Earth & Life Sci Dept Earth Sci NL-1081 HV Amsterdam Netherlands CEA CNRSINSU UVSQ Lab Sci Climat & Environm UMR8212 Gif Sur Yvette France Univ Bristol Sch Geog Sci Bristol BS8 1SS Avon England Univ Wales Sch Archaeol Hist & Anthropol Lampeter SA48 7ED Ceredigion Wales Aberystwyth Univ Dept Geog & Earth Sci Aberystwyth SY23 3DB Dyfed Wales

Since 2010, the INTIMATE (integration of Ice-core, MArine and TErrestrial records) network has been operating as a COST Action (designated ES0907). This paper outlines the accomplishments of the INTIMATE COST Action in the context of how the INTIMATE ideas have evolved during the network's twenty-year life span, and highlights a number of challenges that can guide further work. In the second part of the paper, the contributions that comprise this INTIMATE special issue are introduced. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Age modelling Palaeoclimate data synthesis data-model integration Climate impacts Event stratigraphy Tephra isochrons Leads and lags GRIP GISP2 NGRIP records

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Sea level in time and space: revolutions and inconvenient truths

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JOURNAL OF QUATERNARY SCIENCE 2015年第2期30卷 131-143页

作者： Gehrels, W. Roland Shennan, Ian Univ York Dept Environm York YO10 5DD N Yorkshire England Univ Durham Dept Geog Durham DH1 3LE England

In this paper we identify four revolutions' that in our view have shaped the study of sea-level changes in recent decades. (i) The search for eustasy'. One of the most hotly debated issues in the 1960s is still relevant as models of glacial isostatic adjustment (GIA) require input of the amount of meltwater transferred to the world's oceans following the demise of the large Pleistocene ice sheets. (ii) Resolution of sea-level archives. All sea-level archives have limitations in their resolving power but are we willing to define these? From studies of salt-marsh deposits and corals it is highly likely that climate-driven metre-scale sea-level fluctuations have not occurred during the middle and late Holocene. (iii) Rapid sea-level changes. Improved coring technology has resulted in the suggestion of meltwater pulses during the last deglaciation. Low-frequency high-magnitude events have been documented along seismically active shorelines and provide information on seismic hazards and storm impacts. (iv) Merging of empirical sea-level investigations and models. Much sea-level research in the past two decades has embraced the integration of models and field-derived data, providing testable hypotheses and insights into processes. We conclude with some reminders about the inconvenient truths' that keep the sea-level scientist honest.

关键词： data-model integration eustasy glacial isostatic adjustment Holocene meltwater pulses

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Scaling climate change experiments across space and time

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NEW PHYTOLOGIST 2013年第3期200卷 595-597页

作者： Lee, Hanna Mishurov, Mikhail Natl Ctr Atmospher Res Climate & Global Dynam Div Boulder CO 80307 USA Lund Univ Dept Phys Geog & Ecosyst Sci S-22362 Lund Sweden

Information about several topics discussed at the second ClimMani-Integrated Network for Terrestrial Ecosystem Research on Feedbacks to the Atmosphere and Climate workshop held in Mikulov, Czech Republic in June 2013 on the importance of the terrestrial ecosystem is presened. Topics include drivers of biome shifts, trait responses to environmental change, and scaling of small plots to landscapes. The workshop featured speakers including Melinda Smith, Jordi Sardans and William Hoffman.

关键词： climate change experiments data-model integration environmental gradients extreme climate events leaf traits

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Integrating empirical-modeling approaches to improve understanding of terrestrial ecology processes

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NEW PHYTOLOGIST 2012年第3期195卷 523-525页

作者： McCarthy, Heather R. Luo, Yiqi Wullschleger, Stan D. Univ Oklahoma Dept Bot & Microbiol Norman OK 73019 USA Oak Ridge Natl Lab Div Environm Sci Oak Ridge TN 37831 USA

Information about a workshop held in Maryland in March 2012, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research program on the terrestrial ecology processes is presented. Topics covered at the event from model-assisted experimental design to data driven modeling. Many presenters and participants have suggested the means to promote greater understanding of ecological processes. Some participants have also discussed the Bayesian data assimilation.

关键词： benchmarking data assimilation data-model integration ecological forecasting ecosystem processes global change

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The role of video imagery in predicting daily to monthly coastal evolution

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COASTAL ENGINEERING 2007年第6-7期54卷 539-553页

作者： Smit, M. W. J. Aaminkhof, S. G. J. Wijnberg, K. M. Gonzalez, M. Kingston, K. S. Southgate, H. N. Ruessink, B. G. Holman, R. A. Siegle, E. Davidson, M. Medina, R. Delft Univ Technol Fac Civil Engn & Geosci NL-2600 GA Delft Netherlands Delft Hydraul WL Marine & Coastal Management NL-2600 MH Delft Netherlands Univ Twente Fac Engn Technol Water Engn & Management NL-7500 AE Enschede Netherlands Univ Cantabria Dept Ciencias & Tecn Agua & Medio Ambiente Ocean & Coastal Res Grp E-39005 Santander Spain Univ Plymouth Sch Earth Ocean & Environm Sci Plymouth PL4 8AA Devon England Univ Utrecht Dept Phys Geog Inst Marine & Atmospher Res Utrecht NL-3584 CS Utrecht Netherlands Oregon State Univ Coll Ocean & Atmospher Sci Corvallis OR 97331 USA Univ Sao Paulo Inst Oceanog BR-05508900 Sao Paulo Brazil

Owing to intensified use of the coastal region and the frequent application of small-scale, tailored interventions such as beach nourishments, there is a growing need for coastal state information and knowledge on spatiotemporal scales of meters to kilometers and days to months. The design and implementation of engineering and management measures at these scales is hampered by limited predictability of their impact. Advanced, automated video stations open the door towards the collection of long-term, high-resolution data sets, which offer enhanced opportunities for the prediction of coastal processes at smaller scales. In this paper, the added value of high-resolution data sets for prediction purposes is explored. In particular the application of data-driven approaches as well as process models supported by video data are explored. In the data-driven approach, the inclusion of monthly video-derived data was found to not only improve confidence intervals on the predicted shoreline evolution, but also to facilitate the use of more sophisticated data extrapolation methods. Short-term, operational forecasts of the nearshore flow and sediment transport field were found to benefit from the inclusion of intertidal bathymetric data derived from video imagery. Though in its pioneermg stage for video-based research, it is foreseen that significant advancement in prediction skill will be achieved through development of data-assimilation schemes which combine the best of existing process and empirical knowledge on coastal morphodynamics. (c) 2007 Elsevier B.V. All rights reserved.

关键词： Argus video monitoring coastal state indicator data-driven modelling data-model integration prediction of coastal evolution high-resolution monitoring high-resolution modelling

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