On the stability of the high-latitude climate-vegetation system in a coupled atmosphere-biosphere model

In order to investigate the hypothesis that the Earth's climate and vegetation patterns may have more than one basic state, we use the fully coupled GENESIS-IBIS model. GENESIS is an atmospheric general circulation model. IBIS is a dynamic global vegetation model that integrates biophysical, physiological, and ecological processes. GENESIS and IBIS are coupled by way of a common land surface interface to allow for the full and transient interaction between changes in the vegetation structure and changes in the general circulation of the atmosphere. We examine two modern climate simulations of the coupled model initialized with two different initial conditions. In one case, we initialize the model vegetation cover with the modern observed distribution of vegetation. In the other case, we initialize the vegetation cover with evergreen boreal forests extending to the Arctic coast, replacing high-latitude tundra. We interpret the coupled model's behaviour using a conceptual model for multistability and demonstrate that in both simulations the climate-vegetation system converges to the same equilibrium state. In the present climate, feedbacks between land, ocean, sea ice, and the atmosphere do not result in the warming required to support an expanded boreal forest.     

Impact of CO2 concentration changes on the biosphere-atmosphere system of West Africa

Vegetation dynamics plays a critical role in causing the decadal variability of precipitation over the Sahel region of West Africa. However, the potential impact of changes in CO₂ concentration on vegetation dynamics and precipitation variability of this region has not been addressed by previous studies. In this paper, we explore the role of CO₂ concentration in the regional climate system of West Africa using a zonally symmetric, synchronously coupled biosphere‐atmosphere model. We first document the response of precipitation and vegetation to incremental changes of CO₂ concentration; the impact of CO₂ concentration on the variability of the regional biosphere‐atmosphere system is then addressed using the second half of the twentieth century as an example. An increase of CO₂ concentration causes the regional biosphere‐atmosphere system to become wetter and greener, with the radiative effect of CO₂ and improved plant‐water relation dominant in the Sahelian grassland region and the direct enhancement of leaf carbon assimilation dominant in the tree‐covered region to the south. Driven by the observed sea surface temperature (SST) of the tropical Atlantic Ocean during the period 1950–97 and with CO₂ concentration prescribed at a pre‐industrial level 300ppmv, the model simulates a persistent Sahel drought during the period of 1960s?1990s. The simulated drought takes place in the form of a transition of the coupled biosphere‐atmosphere system from a wet/green regime in the 1950s to a dry/barren regime after the 1960s. This climate transition is triggered by SST forcing and materialized through vegetation‐climate interactions. The same SST forcing does not produce such a persistent drought when a constant modern CO₂ concentration of 350ppmv is specified, indicating that the biosphere‐atmosphere system at higher CO₂ level is more resilient to drought‐inducing external forcings. This finding suggests that the regional climate in Sahel, which tends to alternate between dry and wet spells, may experience longer (or more frequent) wet episodes and shorter (or less frequent) dry episodes in the future than in the past. Our study has significant implications regarding the impact of climate change on regional socio‐economic development.     

The fate of Amazonian ecosystems over the coming century arising from changes in climate,atmospheric CO2, and land use

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO₂ levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias‐corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land‐use change scenarios. We assess the relative roles of climate change, CO₂ fertilization, land‐use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO₂ fertilization will enhance vegetation productivity and alleviate climate‐induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land‐use change and climate‐driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO₂ impacts varies considerably, depending on both the climate and land‐use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors – climate change, CO₂ fertilization effects, fire, and land use – to the fate of the Amazon over the coming century.     

Vegetation controls on northern high latitude snow‐albedo feedback: observations and CMIP5 model simulations

The snow‐masking effect of vegetation exerts strong control on albedo in northern high latitude ecosystems. Large‐scale changes in the distribution and stature of vegetation in this region will thus have important feedbacks to climate. The snow‐albedo feedback is controlled largely by the contrast between snow‐covered and snow‐free albedo (Δα), which influences predictions of future warming in coupled climate models, despite being poorly constrained at seasonal and century time scales. Here, we compare satellite observations and coupled climate model representations of albedo and tree cover for the boreal and Arctic region. Our analyses reveal consistent declines in albedo with increasing tree cover, occurring south of latitudinal tree line, that are poorly represented in coupled climate models. Observed relationships between albedo and tree cover differ substantially between snow‐covered and snow‐free periods, and among plant functional type. Tree cover in models varies widely but surprisingly does not correlate well with model albedo. Furthermore, our results demonstrate a relationship between tree cover and snow‐albedo feedback that may be used to accurately constrain high latitude albedo feedbacks in coupled climate models under current and future vegetation distributions.     

Spatial relationship between climatologies and changes in global vegetation activity

Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land‐cover and climate‐related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982–2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate‐associated effects and a spatially correlated field representing the combined influence of other factors, including land‐use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large‐scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land‐cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).     

Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa

BIOME 6000 is an international project to map vegetation globally at mid‐Holocene (6000 ¹⁴C yr bp ) and last glacial maximum (LGM, 18,000 ¹⁴C yr bp ), with a view to evaluating coupled climate‐biosphere model results. Primary palaeoecological data are assigned to biomes using an explicit algorithm based on plant functional types. This paper introduces the second Special Feature on BIOME 6000. Site‐based global biome maps are shown with data from North America, Eurasia (except South and Southeast Asia) and Africa at both time periods. A map based on surface samples shows the method’s skill in reconstructing present‐day biomes. Cold and dry conditions at LGM favoured extensive tundra and steppe. These biomes intergraded in northern Eurasia. Northern hemisphere forest biomes were displaced southward. Boreal evergreen forests (taiga) and temperate deciduous forests were fragmented, while European and East Asian steppes were greatly extended. Tropical moist forests (i.e. tropical rain forest and tropical seasonal forest) in Africa were reduced. In south‐western North America, desert and steppe were replaced by open conifer woodland, opposite to the general arid trend but consistent with modelled southward displacement of the jet stream. The Arctic forest limit was shifted slighly north at 6000 ¹⁴C yr bp in some sectors, but not in all. Northern temperate forest zones were generally shifted greater distances north. Warmer winters as well as summers in several regions are required to explain these shifts. Temperate deciduous forests in Europe were greatly extended, into the Mediterranean region as well as to the north. Steppe encroached on forest biomes in interior North America, but not in central Asia. Enhanced monsoons extended forest biomes in China inland and Sahelian vegetation into the Sahara while the African tropical rain forest was also reduced, consistent with a modelled northward shift of the ITCZ and a more seasonal climate in the equatorial zone. Palaeobiome maps show the outcome of separate, independent migrations of plant taxa in response to climate change. The average composition of biomes at LGM was often markedly different from today. Refugia for the temperate deciduous and tropical rain forest biomes may have existed offshore at LGM, but their characteristic taxa also persisted as components of other biomes. Examples include temperate deciduous trees that survived in cool mixed forest in eastern Europe, and tropical evergreen trees that survived in tropical seasonal forest in Africa. The sequence of biome shifts during a glacial‐interglacial cycle may help account for some disjunct distributions of plant taxa. For example, the now‐arid Saharan mountains may have linked Mediterranean and African tropical montane floras during enhanced monsoon regimes. Major changes in physical land‐surface conditions, shown by the palaeobiome data, have implications for the global climate. The data can be used directly to evaluate the output of coupled atmosphere‐biosphere models. The data could also be objectively generalized to yield realistic gridded land‐surface maps, for use in sensitivity experiments with atmospheric models. Recent analyses of vegetation‐climate feedbacks have focused on the hypothesized positive feedback effects of climate‐induced vegetation changes in the Sahara/Sahel region and the Arctic during the mid‐Holocene. However, a far wider spectrum of interactions potentially exists and could be investigated, using these data, both for 6000 ¹⁴C yr bp and for the LGM.     

How close are we to a predictive science of the biosphere?

In just 20 years, the field of biosphere-atmosphere interactions has gone from a nascent discipline to a central area of modern climate change research. The development of terrestrial biosphere models that predict the responses of ecosystems to climate and increasing CO2 levels has highlighted several mechanisms by which changes in ecosystem composition and function might alter regional and global climate. However, results from empirical studies suggest that ecosystem responses can differ markedly from the predictions of terrestrial biosphere models. As I discuss here, the challenge now is to connect terrestrial biosphere models to empirical ecosystem measurements. Only by systematically evaluating the predictions of terrestrial biosphere models against suites of ecosystem observations and experiments measurements will a true predictive science of the biosphere be achieved.     

Quantifying the biologically possible range of steady-state soil and surface climates with climate model simulations

The terrestrial biosphere shapes the exchange fluxes of energy and mass at the land surface. The diversity of plant form and functioning can potentially result in a wide variety of possible climatic conditions at the land surface and in the soil, which in turn feed back to more or less suitable conditions for terrestrial productivity. Here, I use sensitivity simulations to vegetation form and functioning with a global climate model to quantify this possible range of steady-states (“PROSS”) of the surface energy-and mass balances. The surface energy-and water balances over land are associated with substantial sensitivity to vegetation parameters, with precipitation varying by more than a factor of 2, and evapotranspiration by a factor of 5. This range in biologically possible climatic conditions is associated with drastically different levels of vegetation productivity. Optimum conditions for maximum productivity are close to the simulated climate of present-day conditions. These results suggest the conclusions that (a) climate does not determine vegetation form and function, but merely constrains it, and (b) the emergent climatic conditions at the land surface seem to be close to optimal for the functioning of the terrestrial biosphere.     

大气CO2升高及气候变化对中国陆地生态系统结构与功能的制约和影响（英文）

在本顶研究中,我们探讨了大气CO2加倍和气候变化条件下,中国陆地生态系统的结构与功能的变化。与多数研究不同的是,我们耦合了两个以地理空间为参照的生态系统模型,即生物地理模型（KBIOME）和生物地球化学模型（TEM）,用此研究现状和未来的环境下,中国的植被分布和年净初级生产力（NPP）的状况,我们采用3个大气环流模型,（GFDL－Q,GISS和OSU）预测的结果代表潜在气候变化。3个气候模型的预测都煌中国将变得更温暖并总体上更湿润。耦合的模型预测中国陆地生态系统的结构与功能都将产生十分显著的变化。植被的变迁表现为：1）中国东部森林带北移,温带常绿阔叶林面积扩大,较南的森林取代较北的类型;2）森林和草地的总面积增加,这是作为取代干旱藻木林、沙漠和高山苔原的结果。年净初级生产力在大气CO2加倍和气候变化条件下,增加30％左右,与其它研究不同的另一点是,我们可能进一步区分生产力变化的原因,在所增加的生产力中,12％－21％是源于生态系统的取代较低产的生态系统的结果。这项研究预测了未来中国植被和生产力潜在的变化并给出了变化的范围,为同类的研究以及有关的政策评估提供了有用的参考信息。     

New coupled model used inversely for reconstructing past terrestrial carbon storage from pollen data: validation of model using modern data

The knowledge of potential impacts of climate change on terrestrial vegetation is crucial to understand long-term global carbon cycle development. Discrepancy in data has long existed between past carbon storage reconstructions since the Last Glacial Maximum by way of pollen, carbon isotopes, and general circulation model (GCM) analysis. This may be due to the fact that these methods do not synthetically take into account significant differences in climate distribution between modern and past conditions, as well as the effects of atmospheric CO₂ concentrations on vegetation. In this study, a new method to estimate past biospheric carbon stocks is reported, utilizing a new integrated ecosystem model (PCM) built on a physiological process vegetation model (BIOME4) coupled with a process-based biospheric carbon model (DEMETER). The PCM was constrained to fit pollen data to obtain realistic estimates. It was estimated that the probability distribution of climatic parameters, as simulated by BIOME4 in an inverse process, was compatible with pollen data while DEMETER successfully simulated carbon storage values with corresponding outputs of BIOME4. The carbon model was validated with present-day observations of vegetation biomes and soil carbon, and the inversion scheme was tested against 1491 surface pollen spectra sample sites procured in Africa and Eurasia. Results show that this method can successfully simulate biomes and related climates at most selected pollen sites, providing a coefficient of determination ( R ) of 0.83–0.97 between the observed and reconstructed climates, while also showing a consensus with an R -value of 0.90–0.96 between the simulated biome average terrestrial carbon variables and the available observations. The results demonstrate the reliability and feasibility of the climate reconstruction method and its potential efficiency in reconstructing past terrestrial carbon storage.     

模拟植物多样性的大尺度分布：从气候和生产力推知的一种可能性（英文）

 鉴于全球植被/生物群区在现状气候条件下已经被很好地模拟并在未来气候变化情景下得到很好的预测,人们有必要和急需模拟大尺度（区域、洲际至全球）植物多样性的分布格局。陆地生物圈模型的发展（从生物地理模型和生物地球化学模型到动态和耦合的植被模型）,气候-生物多样性相互关系和生产力-生物多样性相互关系研究成果的增多,以及基于现有生物多样性调查的全球生物多样性理论和经验制图的进步,加大了模拟大尺度植物多样性格局的可能性。本文的目的是：综述当前气候-生物多样性相互关系和生产力-生物多样性相互关系的主要研究成果以及大尺度     

Sources of Variability in Net Primary Production Predictions at a Regional Scale: A Comparison Using PnET-II and TEM 4.0 in Northeastern US Forests

Because model predictions at continental and global scales are necessarily based on broad characterizations of vegetation, soils, and climate, estimates of carbon stocks and fluxes made by global terrestrial biosphere models may not be accurate for every region. At the regional scale, we suggest that attention can be focused more clearly on understanding the relative strengths of predicted net primary productivity (NPP) limitation by energy, water, and nutrients. We evaluate the sources of variability among model predictions of NPP with a regional-scale comparison between estimates made by PnET-II (a forest ecosystem process model previously applied to the northeastern region) and TEM 4.0 (a terrestrial biosphere model typically applied to the globe) for the northeastern US. When the same climate, vegetation, and soil data sets were used to drive both models, regional average NPP predictions made by PnET-II and TEM were remarkably similar, and at the biome level, model predictions agreed fairly well with NPP estimates developed from field measurements. However, TEM 4.0 predictions were more sensitive to regional variations in temperature as a result of feedbacks between temperature and belowground N availability. In PnET-II, the direct link between transpiration and photosynthesis caused substantial water stress in hardwood and pine forest types with increases in solar radiation; predicted water stress was relieved substantially when soil water holding capacity (WHC) was increased. Increasing soil WHC had little effect on TEM 4.0 predictions because soil water storage was already sufficient to meet plant demand with baseline WHC values, and because predicted N availability under baseline conditions in this region was not limited by water. Because NPP predictions were closely keyed to forest cover type, the relative coverage of low- versus high-productivity forests at both fine and coarse resolutions was an important determinant of regional NPP predictions. Therefore, changes in grid cell size and differences in the methods used to aggregate from fine to coarse resolution were important to NPP predictions insofar as they changed the relative proportions of forest cover. We suggest that because the small patches of high-elevation spruce-fir forest in this region are substantially less productive than forests in the remainder of the region, more accurate NPP predictions will result if models applied to this region use land cover input data sets that retain as much fine-resolution forest type variability as possible. The differences among model responses to variations in climate and soil WHC data sets suggest that the models will respond quite differently to scenarios of future climate. A better understanding of the dynamic interactions between water stress, N availability, and forest productivity in this region will enable models to make more accurate predictions of future carbon stocks and fluxes. Received 19 June 1998; accepted 25 June 1999.     

Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange

Interannual variability in biosphere‐atmosphere exchange of CO₂ is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter‐annual variability in observations. Herein, using standardized data from the North American Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long‐term measurements of biosphere‐atmosphere CO₂ exchange made with eddy‐covariance flux towers at 11 forested sites in North America. Instead of focusing on model‐data agreement we take a systematic, variability‐oriented approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.     

Human modification of the landscape and surface climate in the next fifty years

Human modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land‐cover changes in response to demographic and economic activity. We use the land‐cover scenario as a surface boundary condition in a biophysically‐based land‐surface model coupled to a general circulation model for a 15‐years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land‐cover change relative to the sensitivity to decadal‐scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982–83) and high (1989–90) years to describe the seasonal phenology of the vegetation. In the past several centuries, large‐scale land‐cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land‐cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land‐cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land‐cover change is generally within the range induced by decadal‐scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics.     

A coupled carbon and water flux model to predict vegetation structure

Abstract. A coupled carbon and water flux model (BIOME2) captures the broad-scale environmental controls on the natural distribution of vegetation structural and phenological types in Australia. Model input consists of latitude, soil type, and mean monthly climate (temperature, precipitation, and sunshine hours) data on a 1/10° grid. Model output consists of foliage projective cover (FPC) for the quantitative combination of plant types that maximizes net primary production (NPP). The model realistically simulates changes in FPC along moisture gradients as a consequence of the trade-off between light capture and water stress. A two-layer soil hydrology model also allows simulation of the competitive balance between grass and woody vegetation including the strong effects of soil texture.     

Validation of the Integrated Biosphere Simulator in simulating the potential natural vegetation map of China

The Integrated Biosphere Simulator (IBIS)—a Dynamic Global Vegetation Model—was validated by simulating the potential natural vegetation map of China using data on monthly mean climate from 1961 to 1990, soil texture, and topography. Although the vegetation map simulated by IBIS was able to describe the sketch of vegetation patterns in China, the distributions of several plant functional types (PFTs) and vegetation types were still simulated incorrectly, especially in eastern temperate areas, southern subtropics, the southern Sichuan basin, and the Hengduan mountains area. By adjusting some of the climatic constraints and physiological parameters of PFTs defined in IBIS, the simulated distributions of PFTs became reasonable, and the simulated vegetation map fitted the natural vegetation map better. The kappa statistic between the simulated and the natural vegetation maps was 0.76, an increase of 16.9% from the previous parameter adjustment of 0.65. Correspondingly, the degree of agreement between these two maps rose from “good” to “very good”. After the parameter adjustments, IBIS became more suitable for the large-scale simulation of Chinese natural vegetation distributions and could provide a powerful support to reveal the dynamic responses of terrestrial ecosystems to climate change in China.     

Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems

In terrestrial high‐latitude regions, observations indicate recent changes in snow cover, permafrost, and soil freeze–thaw transitions due to climate change. These modifications may result in temporal shifts in the growing season and the associated rates of terrestrial productivity. Changes in productivity will influence the ability of these ecosystems to sequester atmospheric CO₂. We use the terrestrial ecosystem model (TEM), which simulates the soil thermal regime, in addition to terrestrial carbon (C), nitrogen and water dynamics, to explore these issues over the years 1960–2100 in extratropical regions (30–90°N). Our model simulations show decreases in snow cover and permafrost stability from 1960 to 2100. Decreases in snow cover agree well with National Oceanic and Atmospheric Administration satellite observations collected between the years 1972 and 2000, with Pearson rank correlation coefficients between 0.58 and 0.65. Model analyses also indicate a trend towards an earlier thaw date of frozen soils and the onset of the growing season in the spring by approximately 2–4 days from 1988 to 2000. Between 1988 and 2000, satellite records yield a slightly stronger trend in thaw and the onset of the growing season, averaging between 5 and 8 days earlier. In both, the TEM simulations and satellite records, trends in day of freeze in the autumn are weaker, such that overall increases in growing season length are due primarily to earlier thaw. Although regions with the longest snow cover duration displayed the greatest increase in growing season length, these regions maintained smaller increases in productivity and heterotrophic respiration than those regions with shorter duration of snow cover and less of an increase in growing season length. Concurrent with increases in growing season length, we found a reduction in soil C and increases in vegetation C, with greatest losses of soil C occurring in those areas with more vegetation, but simulations also suggest that this trend could reverse in the future. Our results reveal noteworthy changes in snow, permafrost, growing season length, productivity, and net C uptake, indicating that prediction of terrestrial C dynamics from one decade to the next will require that large‐scale models adequately take into account the corresponding changes in soil thermal regimes.     

Impulse response functions of terrestrial carbon cycle models: method and application

To provide a common currency for model comparison, validation and manipulation, we suggest and describe the use of impulse response functions, a concept well-developed in other fields, but only partially developed for use in terrestrial carbon cycle modelling. In this paper, we describe the derivation of impulse response functions, and then examine (i) the dynamics of a simple five-box biosphere carbon model; (ii) the dynamics of the CASA biosphere model, a spatially explicit NPP and soil carbon biogeochemistry model; and (iii) various diagnostics of the two models, including the latitudinal distribution of mean age, mean residence time and turnover time. We also (i) deconvolve the past history of terrestrial NPP from an estimate of past carbon sequestration using a derived impulse response function to test the performance of impulse response functions during periods of historical climate change; (ii) convolve impulse response functions from both the simple five-box model and the CASA model against a historical record of atmospheric δ¹³C to estimate the size of the terrestrial ¹³C isotopic disequilibrium; and (iii) convolve the same impulse response functions against a historical record of atmospheric ¹⁴C to estimate the ¹⁴C content and isotopic disequilibrium of the terrestrial biosphere at the 1° × 1° scale. Given their utility in model comparison, and the fact that they facilitate a number of numerical calculations that are difficult to perform with the complex carbon turnover models from which they are derived, we strongly urge the inclusion of impulse response functions as a diagnostic of the perturbation response of terrestrial carbon cycle models.     

Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model

The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO₂ concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO₂. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.     

A new global biome reconstruction and data-model comparison for the Middle Pliocene

Aim To produce a robust, comprehensive global biome reconstruction for the Middle Pliocene (c. 3.6–2.6 Ma), which is based on an internally consistent palaeobotanical data set and a state‐of‐the‐art coupled climate–vegetation model. The reconstruction gives a more rigorous picture of climate and environmental change during the Middle Pliocene and provides a new boundary condition for future general circulation model (GCM) studies. Location Global. Methods Compilation of Middle Pliocene vegetation data from 202 marine and terrestrial sites into the comprehensive GIS data base TEVIS (Tertiary Environmental Information System). Translation into an internally consistent classification scheme using 28 biomes. Comparison and synthesis of vegetation reconstruction from palaeodata with the outputs of the mechanistically based BIOME4 model forced by climatology derived from the HadAM3 GCM. Results The model results compare favourably with available palaeodata and highlight the importance of employing vegetation–climate feedbacks and the anomaly method in biome models. Both the vegetation reconstruction from palaeobotanical data and the BIOME4 prediction indicate a general warmer and moister climate for the Middle Pliocene. Evergreen taiga as well as temperate forest and grassland shifted northward, resulting in much reduced tundra vegetation. Warm‐temperate forests (with subtropical taxa) spread in mid and eastern Europe and tropical savannas and woodland expanded in Africa and Australia at the expense of deserts. Discrepancies which occurred between data reconstruction and model simulation can be related to: (1) poor spatial model resolution and data coverage; (2) uncertainties in delimiting biomes using climate parameters; or (3) uncertainties in model physics and/or geological boundary conditions. Main conclusions The new global biome reconstruction combines vegetation reconstruction from palaeobotanical proxies with model simulations. It is an important contribution to the further understanding of climate and vegetation changes during the Middle Pliocene warm interval and will enhance our knowledge about how vegetation may change in the future.