Publications
431 results found
Hickler T, Prentice IC, Smith B, et al., 2006, Implementing plant hydraulic architecture within the LPJ Dynamic Global Vegetation Model, GLOBAL ECOLOGY AND BIOGEOGRAPHY, Vol: 15, Pages: 567-577, ISSN: 1466-822X
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- Citations: 124
Le Quéré C, Prentice IC, Rivkin RB, 2006, Modeling interactions between marine ecosystems and climate, Eos, Vol: 87, ISSN: 0096-3941
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- Citations: 2
Scholze M, Knorr W, Arnell NW, et al., 2006, A climate-change risk analysis for world ecosystems, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 103, Pages: 13116-13120, ISSN: 0027-8424
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- Citations: 450
Zaehle S, Sitch S, Prentice IC, et al., 2006, The importance of age-related decline in forest NPP for modeling regional carbon balances, ECOLOGICAL APPLICATIONS, Vol: 16, Pages: 1555-1574, ISSN: 1051-0761
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- Citations: 107
Ni J, Harrison SP, Prentice IC, et al., 2006, Impact of climate variability on present and Holocene vegetation: A model-based study, ECOLOGICAL MODELLING, Vol: 191, Pages: 469-486, ISSN: 0304-3800
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- Citations: 46
Schaphoff S, Lucht W, Gerten D, et al., 2006, Terrestrial biosphere carbon storage under alternative climate projections, CLIMATIC CHANGE, Vol: 74, Pages: 97-122, ISSN: 0165-0009
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- Citations: 121
Morales P, Sykes MT, Prentice IC, et al., 2005, Comparing and evaluating process-based ecosystem model predictions of carbon and water fluxes in major European forest biomes, GLOBAL CHANGE BIOLOGY, Vol: 11, Pages: 2211-2233, ISSN: 1354-1013
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- Citations: 213
Schröter D, Cramer W, Leemans R, et al., 2005, Ecosystem service supply and vulnerability to global change in Europe, SCIENCE, Vol: 310, Pages: 1333-1337, ISSN: 0036-8075
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- Citations: 1178
Le Quéré C, Harrison SP, Prentice IC, et al., 2005, Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models, Global Change Biology, Vol: 11, Pages: 2016-2040, ISSN: 1354-1013
Ecosystem processes are important determinants of the biogeochemistry of the ocean, and they can be profoundly affected by changes in climate. Ocean models currently express ecosystem processes through empirically derived parameterizations that tightly link key geochemical tracers to ocean physics. The explicit inclusion of ecosystem processes in models will permit ecological changes to be taken into account, and will allow us to address several important questions, including the causes of observed glacial-interglacial changes in atmospheric trace gases and aerosols, and how the oceanic uptake of CO2 is likely to change in the future. There is an urgent need to assess our mechanistic understanding of the environmental factors that exert control over marine ecosystems, and to represent their natural complexity based on theoretical understanding. We present a prototype design for a Dynamic Green Ocean Model (DGOM) based on the identification of (a) key plankton functional types that need to be simulated explicitly to capture important biogeochemical processes in the ocean; (b) key processes controlling the growth and mortality of these functional types and hence their interactions; and (c) sources of information necessary to parameterize each of these processes within a modeling framework. We also develop a strategy for model evaluation, based on simulation of both past and present mean state and variability, and identify potential sources of validation data for each. Finally, we present a DGOM-based strategy for addressing key questions in ocean biogeochemistry. This paper thus presents ongoing work in ocean biogeochemical modeling, which, it is hoped will motivate international collaborations to improve our understanding of the role of the ocean in the climate system. © 2005 Blackwell Publishing Ltd.
Le Quéré C, Harrison SP, Prentice IC, et al., 2005, Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models, GLOBAL CHANGE BIOLOGY, Vol: 11, Pages: 2016-2040, ISSN: 1354-1013
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- Citations: 602
Spessa A, McBeth B, Prentice C, 2005, Relationships among fire frequency, rainfall and vegetation patterns in the wet-dry tropics of northern Australia: An analysis based on NOAA-AVHRR data, Global Ecology and Biogeography, Vol: 14, Pages: 439-454, ISSN: 1466-822X
Aim To quantify the regional-scale spatio-temporal relationships among rainfall, vegetation and fire frequency in the Australian wet-dry tropics (AWDT). Location Northern Australia: Cape York Peninsula, central Arnhem, central Kimberly, Einasleigh Uplands, Gulf Fall Uplands and northern Kimberley. Methods Monthly 'fraction of photosynthetic active radiation absorbed by green vegetation' (fAPAR) was decomposed into monthly evergreen (EG) and monthly raingreen (RG) components using time-series techniques applied to monthly normalized difference vegetation index (NDVI) data from Advanced Very High Resolution Radiometer (AVHRR) imagery. Fire affected areas were independently mapped at the same spatio-temporal resolution from AVHRR imagery. Weather station records were spatially interpolated to create monthly rainfall surfaces. Vegetation structural classes were derived from a digitized map of northern Australian vegetation communities (1:1,000,000). Generalized linear models were used to quantify relationships among the fAPAR, EG and RG signals, vegetation structure, rainfall and fire frequency, for the period November 1996-December 2001. Results The fAPAR and EG signals are positively correlated with annual rainfall and canopy cover, notably: EGclosed forest > EG open heathland > EGopen forest > EG woodland > EGopen woodland > EG low woodland > EGlow open woodland > EG open grassland· Vegetation height and fAPAR are positively correlated, excluding the special case of open heathland. The RG signal is highest where intermediate annual rainfall and strong seasonality in rainfall coincide, and is associated with vegetation structure as follows: RG open grassland > RGwoodland > RG open forest > RGopen heathland > RG low woodland > RGopen woodland > RG low open woodland > RGclosed forset · Monthly RG tracks monthly rainfall. Annual proportion of area burnt (PB) is maximal where high RG coincides with low EG (open grass
Notaro M, Liu ZY, Gallimore R, et al., 2005, Simulated and observed preindustrial to modern vegetation and climate changes, JOURNAL OF CLIMATE, Vol: 18, Pages: 3650-3671, ISSN: 0894-8755
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- Citations: 35
Thonicke K, Prentice IC, Hewitt C, 2005, Modeling glacial-interglacial changes in global fire regimes and trace gas emissions, GLOBAL BIOGEOCHEMICAL CYCLES, Vol: 19, ISSN: 0886-6236
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- Citations: 34
Foley JA, DeFries R, Asner GP, et al., 2005, Global consequences of land use, SCIENCE, Vol: 309, Pages: 570-574, ISSN: 0036-8075
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- Citations: 7971
Thuiller W, Lavorel S, Araújo MB, et al., 2005, Climate change threats to plant diversity in Europe, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 102, Pages: 8245-8250, ISSN: 0027-8424
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- Citations: 1639
Krinner G, Viovy N, de Noblet-Ducoudré N, et al., 2005, A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system -: art. no. GB1015, GLOBAL BIOGEOCHEMICAL CYCLES, Vol: 19, ISSN: 0886-6236
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- Citations: 1450
Knorr W, Prentice IC, House JI, et al., 2005, Long-term sensitivity of soil carbon turnover to warming, NATURE, Vol: 433, Pages: 298-301, ISSN: 0028-0836
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- Citations: 905
Wania R, Prentice C, Harrison S, et al., 2004, The role of natural wetlands in the global methane cycle, ISSN: 0096-3941
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- Citations: 5
Kittel TGF, Rosenbloom NA, Royle JA, et al., 2004, VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA, Climate Research, Vol: 27, Pages: 151-170, ISSN: 0936-577X
Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5° latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate an
Barboni D, Harrison SP, Bartlein PJ, et al., 2004, Relationships between plant traits and climate in the Mediterranean region:: A pollen data analysis, JOURNAL OF VEGETATION SCIENCE, Vol: 15, Pages: 635-646, ISSN: 1100-9233
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- Citations: 67
Pickett EJ, Harrison SP, Hope G, et al., 2004, Pollen-based reconstructions of biome distributions for Australia, Southeast Asia and the Pacific (SEAPAC region) at 0, 6000 and 18,000 <SUP>14</SUP>C yr BP, JOURNAL OF BIOGEOGRAPHY, Vol: 31, Pages: 1381-1444, ISSN: 0305-0270
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- Citations: 110
Gerber S, Joos F, Prentice IC, 2004, Sensitivity of a dynamic global vegetation model to climate and atmospheric CO<sub>2</sub>, GLOBAL CHANGE BIOLOGY, Vol: 10, Pages: 1223-1239, ISSN: 1354-1013
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- Citations: 54
Joos F, Gerber S, Prentice IC, et al., 2004, Transient simulations of Holocene atmospheric carbon dioxide and terrestrial carbon since the Last Glacial Maximum, GLOBAL BIOGEOCHEMICAL CYCLES, Vol: 18, ISSN: 0886-6236
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- Citations: 152
Ni J, Sykes MT, Prentice IC, et al., 2004, Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3 (vol 9, pg 463, 2000), GLOBAL ECOLOGY AND BIOGEOGRAPHY, Vol: 13, Pages: 189-189, ISSN: 0960-7447
TER BRAAK CJF, PRENTICE IC, 2004, A Theory of Gradient Analysis, Advances in Ecological Research, Vol: 34, Pages: 235-282, ISSN: 0065-2504
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- Citations: 105
Prentice IC, Le Quéré C, Buitenhuis ET, et al., 2004, Biosphere dynamics:: Challenges for Earth system models, 23rd General Assembly of the International-Union-of-Geodesy-and Geophysics, Publisher: AMER GEOPHYSICAL UNION, Pages: 269-278, ISSN: 0065-8448
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- Citations: 6
Bigelow NH, Brubaker LB, Edwards ME, et al., 2003, Climate change and Arctic ecosystems: 1. Vegetation changes north of 55°N between the last glacial maximum, mid-Holocene, and present, Journal of Geophysical Research: Atmospheres, Vol: 108, ISSN: 0148-0227
A unified scheme to assign pollen samples to vegetation types was used to reconstruct vegetation patterns north of 55°N at the last glacial maximum (LGM) and mid-Holocene (6000 years B.P.). The pollen data set assembled for this purpose represents a comprehensive compilation based on the work of many projects and research groups. Five tundra types (cushion forb tundra, graminoid and forb tundra, prostrate dwarf-shrub tundra, erect dwarf-shrub tundra, and low- and high-shrub tundra) were distinguished and mapped on the basis of modern pollen surface samples. The tundra-forest boundary and the distributions of boreal and temperate forest types today were realistically reconstructed. During the mid-Holocene the tundra-forest boundary was north of its present position in some regions, but the pattern of this shift was strongly asymmetrical around the pole, with the largest northward shift in central Siberia (∼200 km), little change in Beringia, and a southward shift in Keewatin and Labrador (∼200 km). Low- and high-shrub tundra extended farther north than today. At the LGM, forests were absent from high latitudes. Graminoid and forb tundra abutted on temperate steppe in northwestern Eurasia while prostrate dwarf-shrub, erect dwarf-shrub, and graminoid and forb tundra formed a mosaic in Beringia. Graminoid and forb tundra is restricted today and does not form a large continuous biome, but the pollen data show that it was far more extensive at the LGM, while low- and high-shrub tundra were greatly reduced, illustrating the potential for climate change to dramatically alter the relative areas occupied by different vegetation types.
Kaplan JO, Bigelow NH, Prentice IC, et al., 2003, Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections, Journal of Geophysical Research: Atmospheres, Vol: 108, ISSN: 0148-0227
Large variations in the composition, structure, and function of Arctic ecosystems are determined by climatic gradients, especially of growing-season warmth, soil moisture, and snow cover. A unified circumpolar classification recognizing five types of tundra was developed. The geographic distributions of vegetation types north of 55°N, including the position of the forest limit and the distributions of the tundra types, could be predicted from climatology using a small set of plant functional types embedded in the biogeochemistry-biogeography model BIOME4. Several palaeoclimate simulations for the last glacial maximum (LGM) and mid-Holocene were used to explore the possibility of simulating past vegetation patterns, which are independently known based on pollen data. The broad outlines of observed changes in vegetation were captured. LGM simulations showed the major reduction of forest, the great extension of graminoid and forb tundra, and the restriction of low- and high-shrub tundra (although not all models produced sufficiently dry conditions to mimic the full observed change). Mid-Holocene simulations reproduced the contrast between northward forest extension in western and central Siberia and stability of the forest limit in Beringia. Projection of the effect of a continued exponential increase in atmospheric CO2 concentration, based on a transient ocean-atmosphere simulation including sulfate aerosol effects, suggests a potential for larger changes in Arctic ecosystems during the 21st century than have occurred between mid-Holocene and present. Simulated physiological effects of the CO2 increase (to > 700 ppm) at high latitudes were slight compared with the effects of the change in climate.
Kaplan JO, Bigelow NH, Prentice IC, et al., 2003, Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 108, ISSN: 2169-897X
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- Citations: 365
Bigelow NH, Brubaker LB, Edwards ME, et al., 2003, Climate change and Arctic ecosystems:: 1.: Vegetation changes north of 55°N between the last glacial maximum, mid-Holocene, and present -: art. no. 8170, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 108, ISSN: 2169-897X
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- Citations: 207
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