Biome Model Research Articles

Projected future climatic forcing on the global distribution of vegetation types.

Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Simulated dust activity in typical time periods of the past 250 million years

The dust cycle in three typical time periods of the past 250 Myr, namely 240 Ma, 130 Ma and 80 Ma, is studied using the climate model CESM1.2.2 combined with the vegetation model BIOME4 and compared with that of the present day. The atmospheric dust loading obtained for these three periods is 35.9, 9.7 and 3.2 Tg, respectively. In comparison, the present-day dust loading is ∼24 Tg. It is found that the area of subtropical land is the major controlling factor in the variation of dust loading; the climate and the land plant evolution play a relatively minor role in these experiments where continental ice sheets are not considered and the reliability of BIOME4 in simulating vegetation of deep time is still uncertain. Although the simulated atmospheric dust loading in 240 Ma was much higher than that simulated for today, the fraction of dust deposited into the ocean (26%) was much lower due to its supercontinental configuration. Dust was able to cool the local annual mean surface temperature by a maximum of 2 °C in 240 Ma. A warming is obtained in the northern polar region in both 240 Ma and 130 Ma, likely due to strengthened meridional oceanic heat transport rather than due to snow darkening.

Improving biome and climate modelling for a set of past climate conditions: evaluating bias correction using the CDF-t approach

Climate model simulations are inherently biased. It is a notably difficult problem when dealing with climate impact assessments and model-data integration. This is especially true when looking at derived quantities such as biomes, where not only climate but also vegetation dynamics biases come into play. To overcome such difficulties, we evaluate the performance of an existing methodology to correct climate model outputs, applied here for the first time to long past climate conditions. The proposed methodology relies on the ‘Cumulative Distribution Function-transform’ (CDF-t) technique, which allows to account for climate change within the bias-correction procedure. The results are evaluated in two independent ways: (i) using forward modelling, so that model results are directly comparable to reconstructed vegetation distribution; (ii) using climatic reconstructions based on an inverse modelling approach. The modelling is performed using the intermediate complexity model iLOVECLIM in the standard global and interactively downscaled over the Europe version. The combined effects of dynamical downscaling and bias correction resulted in significantly stronger agreement between the simulated results and pollen-based biome reconstructions (BIOME6000) for the pre-industrial (0.18 versus 0.44) and mid-Holocene (MH) (0.31 versus 0.40). Higher correlation is also observed between statistically modelled global gridded potential natural distribution and modelled biomes (0.36 versus 0.41). Similarly, we find higher correlation between the reconstructed and the modelled temperatures for the MH (0.02 versus 0.21). No significant difference is found for the Last Glacial Maximum when using temperature reconstructions, due to the low number of data points available. Our findings show that the application of the CDF-t method on simulated climate variables enables us to simulate palaeoclimate and vegetation distribution in better agreement with independent reconstructions.

A spatiotemporally explicit paleoenvironmental framework for the Middle Stone Age of eastern Africa

Eastern Africa has played a prominent role in debates about human evolution and dispersal due to the presence of rich archaeological, palaeoanthropological and palaeoenvironmental records. However, substantial disconnects occur between the spatial and temporal resolutions of these data that complicate their integration. Here, we apply high-resolution climatic simulations of two key parameters, mean annual temperature and precipitation, and a biome model, to produce a highly refined characterisation of the environments inhabited during the eastern African Middle Stone Age. Occupations are typically found in sub-humid climates and landscapes dominated by or including tropical xerophytic shrubland. Marked expansions from these core landscapes include movement into hotter, low-altitude landscapes in Marine Isotope Stage 5 and cooler, high-altitude landscapes in Marine Isotope Stage 3, with the recurrent inhabitation of ecotones between open and forested habitats. Through our use of high-resolution climate models, we demonstrate a significant independent relationship between past precipitation and patterns of Middle Stone Age stone tool production modes overlooked by previous studies. Engagement with these models not only enables spatiotemporally explicit examination of climatic variability across Middle Stone Age occupations in eastern Africa but enables clearer characterisation of the habitats early human populations were adapted to, and how they changed through time.

Reconstructing the distribution of the paleobiome types in the Three-River Headwaters Region in China from the middle Holocene

This study examined the spatial and temporal patterns of the paleobiome types in the Three-River Headwaters Region (TRHR, Sanjiangyuan) in China from the middle Holocene (i.e. 6000 BP). Existing studies explored the patterns of paleobiome types by identifying the type of biomes in pollen sites, based on the taxonomical assemblage of pollen samples. This site-wise identification, however, is not suited for the analysis of the TRHR because pollen sites in the region-level are discrete and low-resolution. In this study – to solve the lack of the pollen sites – climate data, which are easy to interpolate, were extracted from the pollen data by pollen transfer functions. Next, the extracted climate data were calibrated and interpolated over the TRHR and study period. Then, a physiological biome model based on climate was used to produce the chronology of the distribution of the biome types. Consequently, the chronology was reconstructed with a time interval of 50 years and a spatial cell size of 0.5 ° × 0.5 °. From the results, the variations in the distribution of the paleobiome types were mainly dominated by 36 patterns over 10 biome types. In detail, tundra and semidesert were the main types, and the alternation of these two types was the main pattern. Further, the long-term evolution was from tundra to semi-desert, and the precipitation was the main driving force for changes in biomes, while temperature also had some influence.

Dispersal Increases the Resilience of Tropical Savanna and Forest Distributions.

Global change may induce changes in savanna and forest distributions, but the dynamics of these changes remain unclear. Classical biome theory suggests that climate is predictive of biome distributions, such that shifts will be continuous and reversible. This view, however, cannot explain the overlap in the climatic ranges of tropical biomes, which some argue may result from fire-vegetation feedbacks, maintaining savanna and forest as bistable states. Under this view, biome shifts are argued to be discontinuous and irreversible. Mean-field bistable models, however, are also limited, as they cannot reproduce the spatial aggregation of biomes. Here we suggest that both models ignore spatial processes, such as dispersal, which may be important when savanna and forest abut. We examine the contributions of dispersal to determining biome distributions using a 2D reaction-diffusion model, comparing results qualitatively to empirical savanna and forest distributions in sub-Saharan Africa. We find that the diffusion model resolves both the aforementioned limitations of biome models. First, local dispersive spatial interactions, with an underlying precipitation gradient, can reproduce the spatial aggregation of biomes with a stable savanna-forest boundary. Second, the boundary is determined not only by the amount of precipitation but also by the geometrical shape of the precipitation contours. These geometrical effects arise from continental-scale source-sink dynamics, which reproduce the mismatch between biome and climate. Dynamically, the spatial model predicts that dispersal may increase the resilience of tropical biome in response to global change: the boundary continuously tracks climate, recovering following disturbances, unless the remnant biome patches are too small.

Oligocene vegetation of Europe and western Asia—Diversity change and continental patterns reflected by plant functional types

Spatial vegetation patterns potentially reflect coeval continental climate variations which are also impacted by palaeogeographical settings. Plant functional types (PFTs) and their distribution, frequently applied in ecological studies and biome modelling, serve as a tool for reconstructing palaeovegetation units and ultimately tracing palaeoecological/climate gradients. Earlier quantitative studies focusing on distribution patterns of PFTs and designed to put forward data‐model comparisons were carried out on well‐dated Middle and Late Miocene floras. Moreover, the PFT approach has been successfully applied to reconstruct Eocene vegetation patterns in several time slices at a global scale as well as in regional vegetation reconstructions throughout the Cenozoic. In the current study, a PFT approach with 41 different classes is applied on Rupelian and Chattian fossil floras of Europe and western Asia to infer spatial vegetation differences across the study area. A comprehensive palaeobotanical record including ~163 macro‐ (leaves, fruits and seeds) and microfloras was compiled. The floristic components of these palaeofloras are translated to PFTs including herbaceous to arboreal classes. The PFTs are defined using traits and climatic thresholds of key taxa, and comprise species assigned by morphological and phenological features with respect to the related ecosystem. Diversity values of each PFT are calculated for the fossil floras and spatial gradients over western Eurasia are investigated for the Rupelian and Chattian. PFT diversity maps and transects for both time slices reveal basic patterns of the vegetational structure at the continental scale. It is shown that in both time slices studied tropical and broadleaved evergreen PFTs were more diverse in the West and at lower latitudes. Consistently with the global climate evolution as known from marine archives and regional continental records their level was higher in the Rupelian compared to the Chattian. All over low diversities of xeric PFTs coincide with the previously assumed dominance of humid climate conditions in western Eurasia throughout the Oligocene, however, the reconstructed spatial gradients suggest somewhat drier conditions to the southwest and southeast of the study area.

Reconstructing Palaeoarchaean microbial biomes flourishing in the presence of emergent landmasses using trace and rare earth element systematics

Palaeoarchaean cherts preserve the most ancient direct traces of life, but this palaeobiological testament is rarely assimilated into ecosystem or biome models. Trace and rare earth element plus yttrium (REE + Y) compositions reliably decode the palaeodepositional settings of these cherts, and thus constrain the environments within which early microbial life flourished. Herein, we present systematic comparisons between bulk inductively coupled plasma mass spectrometry (ICP-MS) of four fossiliferous cherts from the Barberton greenstone belt, South Africa (the 3.472 Ga Middle Marker horizon, 3.45 Ga Hooggenoeg H5c chert, 3.334 Ga Footbridge Chert, and ~3.33 Ga Josefsdal Chert), and in situ laser ablation (LA) ICP-MS transects through microbial laminations therein. Normalised bulk ICP-MS analyses generally exhibit fractionated REE + Y patterns typical of anoxic hydrogenous sedimentation, supporting previous assertions that the Palaeoarchaean habitable realm was a hydrothermally influenced ocean. Suppressed La, Eu and Y anomalies, together with supra-chondritic Y/Ho ratios, however, indicate restriction from the open ocean and influences from non-marine waters. In situ LA ICP-MS transects through fossiliferous layers yield flat, light REE-enriched REE + Y patterns and chondritic Y/Ho ratios indicating major contributions from terrigenous, riverine fluids, i.e. continental weathering. Resurgences of marine chemistry (increased Y/Ho ratios, La and Y anomalies) occur within microbial laminations themselves. Combined, these results evidence the presence of emergent, volcanic landmasses in the Palaeoarchaean, and highlight the importance of epicontinental basins atop these landmasses as loci for microbial biomes up to 250 Ma before large-scale terrestrial ecosystems. Increased riverine weathering of mafic-felsic continental material, together with periodic seawater recharge into these basins, generated disequilibrium redox conditions under which microbial life flourished. Emergent landmasses may thus have catalysed the flourishing of widespread productive photosynthetic biomes. Charting the relative dominance of biomes through time could illuminate microbial evolutionary trajectories through the lens of environmental reconstruction. Furthermore, we advocate the use of correlated bulk and in situ geochemical approaches in reconstructing ancient environments, since signals relating to small-scale palaeoenvironmental fluctuation can evidently be masked by bulk rock chemistry.

The Early Holocene vegetation changes in the vicinity of the Gorbunovo peat bog in the Middle Urals (Russia)

The paper presents the results of a comprehensive palaeobotanical research of lacustrine and peat deposits of archaeological Mesolithic sites discovered at the Gorbunovo peat bog (Middle Urals). Pollen and plant macrofossil data, as well as a biome model were used to describe the vegetation changes in the study area in the Early Holocene. It was found out that in the second half of the Pre-Boreal and the first half of the Boreal periods of the Early Holocene (approximately to 9,800–9,600 cal BP), the vicinity of the Gorbunovo peat bog was dominated by cold deciduous forests. Larch, spruce-larch and birch forests and meadow communities with periglacial elements were widespread. Various aquatic plants could be found in the pond, though it started to turn into swamp. In the second half of the Boreal period (approximately at 9,600–9,500 cal BP), the taiga biome, including pine and birch-pine forests with occurrence of spruce started to prevail. Periglacial communities became degraded. Aggressive water logging led to the formation of a peat bog.

Northern Hemisphere biome changes (>30°N) since 40 cal ka BP and their driving factors inferred from model-data comparisons

Ongoing and past biome transitions are generally assigned to climate and atmospheric changes (e.g. temperature, precipitation, CO2), but the major regional factors or factor combinations that drive vegetation change often remain unknown. Modelling studies applying ensemble runs can help to partition the effects of the different drivers. Such studies require careful validation with observational data. In this study, fossil pollen records from 741 sites in Europe, 728 sites in North America, and 418 sites in Asia (extracted from terrestrial archives including lake sediments) are used to reconstruct biomes at selected time slices between 40 cal ka BP (calibrated thousand years before present) and today. These results are used to validate Northern Hemisphere biome distributions (>30°N) simulated by the biome model BIOME4 that has been forced with climate data simulated by a General Circulation model. Quantitative comparisons between pollen- and model-based results show a generally good fit at a broad spatial scale. Mismatches occur in central-arid Asia with a broader extent of grassland throughout the last 40 ka (likely due to the over-representation of Artemisia and Chenopodiaceae pollen) and in Europe with over-estimation of tundra at 0 cal ka BP (likely due to human impacts to some extent). Sensitivity analysis reveals that broad-scale biome changes follow the global signal of major postglacial temperature change, although the climatic variables vary in their regional and temporal importance. Temperature is the dominant variable in Europe and other rather maritime areas for biome changes between 21 and 14 ka, while precipitation is highly important in the arid inland regions of Asia and North America. The ecophysiological effect of changes in the atmospheric CO2-concentration has the highest impact during this transition than in other intervals. With respect to modern vegetation in the course of global warming, our findings imply that vegetation change in the Northern Hemisphere may be strongly limited by effective moisture changes, i.e. the combined effect of temperature and precipitation, particularly in inland areas.

Harmonising plant functional type distributions for evaluating Earth system models

Abstract. Dynamic vegetation models simulate global vegetation in terms of fractional coverage of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based vegetation reconstructions are initially only available in the form of time series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based vegetation reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonise PFT distributions by assigning them into nine mega-biomes, using only assumptions on the minimum PFT cover fractions and few bioclimatic constraints (based on the 2 m temperature). These constraints mainly follow the limitation rules used in the classical biome models (here BIOME4). We test the method for six state-of-the-art dynamic vegetation models that are included in Earth system models based on pre-industrial, mid-Holocene and Last Glacial Maximum simulations. The method works well, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are generally better represented than regionally confined biomes (warm–temperate forest, savanna). The comparison with biome distributions inferred via the classical biomisation approach of forcing biome models (here BIOME1) with the simulated climate states shows that the PFT-based biomisation is even able to keep up with the classical method. However, as the new method considers the PFT distributions actually calculated by the Earth system models, it allows for a direct comparison and evaluation of simulated vegetation distributions which the classical method cannot do. Thereby, the new method provides a powerful tool for the evaluation of Earth system models in general.

Biome changes and their inferred climatic drivers in northern and eastern continental Asia at selected times since 40 cal ka bp

Recent global warming is pronounced in high-latitude regions (e.g. northern Asia), and will cause the vegetation to change. Future vegetation trends (e.g. the “arctic greening”) will feed back into atmospheric circulation and the global climate system. Understanding the nature and causes of past vegetation changes is important for predicting the composition and distribution of future vegetation communities. Fossil pollen records from 468 sites in northern and eastern Asia were biomised at selected times between 40 cal ka bp and today. Biomes were also simulated using a climate-driven biome model and results from the two approaches compared in order to help understand the mechanisms behind the observed vegetation changes. The consistent biome results inferred by both approaches reveal that long-term and broad-scale vegetation patterns reflect global- to hemispheric-scale climate changes. Forest biomes increase around the beginning of the late deglaciation, become more widespread during the early and middle Holocene, and decrease in the late Holocene in fringe areas of the Asian Summer Monsoon. At the southern and southwestern margins of the taiga, forest increases in the early Holocene and shows notable species succession, which may have been caused by winter warming at ca. 7 cal ka bp. At the northeastern taiga margin (central Yakutia and northeastern Siberia), shrub expansion during the last deglaciation appears to prevent the permafrost from thawing and hinders the northward expansion of evergreen needle-leaved species until ca. 7 cal ka bp. The vegetation-climate disequilibrium during the early Holocene in the taiga-tundra transition zone suggests that projected climate warming will not cause a northward expansion of evergreen needle-leaved species.

Regional contribution to variability and trends of global gross primary productivity

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000–2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr−1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr−1), and close to the MTE (120 Pg C yr−1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Photosynthetic productivity and its efficiencies in ISIMIP2a biome models: benchmarking for impact assessment studies

Simulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of global GPP simulated by eight biome models participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) with four meteorological forcing datasets (30 simulations), using independent GPP estimates and recent satellite data of solar-induced chlorophyll fluorescence as a proxy of GPP. The simulated global terrestrial GPP ranged from 98 to 141 Pg C yr−1 (1981–2000 mean); considerable inter-model and inter-data differences were found. Major features of spatial distribution and seasonal change of GPP were captured by each model, showing good agreement with the benchmarking data. All simulations showed incremental trends of annual GPP, seasonal-cycle amplitude, radiation-use efficiency, and water-use efficiency, mainly caused by the CO2 fertilization effect. The incremental slopes were higher than those obtained by remote sensing studies, but comparable with those by recent atmospheric observation. Apparent differences were found in the relationship between GPP and incoming solar radiation, for which forcing data differed considerably. The simulated GPP trends co-varied with a vegetation structural parameter, leaf area index, at model-dependent strengths, implying the importance of constraining canopy properties. In terms of extreme events, GPP anomalies associated with a historical El Niño event and large volcanic eruption were not consistently simulated in the model experiments due to deficiencies in both forcing data and parameterized environmental responsiveness. Although the benchmarking demonstrated the overall advancement of contemporary biome models, further refinements are required, for example, for solar radiation data and vegetation canopy schemes.

Benchmarking carbon fluxes of the ISIMIP2a biome models

The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). We evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (ELUC) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (), and 2) the land CO2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as FJena and FCAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasing Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, FJena and FCAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.

Biome changes in Asia since the mid-Holocene – an analysis of different transient Earth system model simulations

Abstract. The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate–vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere–ocean(–vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon–westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5 to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert–steppe margin is shifted westward by 5° (1–9° in the individual simulations). The forest biomes are expanded north-westward by 2°, ranging from 0 to 4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.

Evaluation of global warming impacts on the carbon budget of terrestrial ecosystems in monsoon Asia: a multi‐model analysis

AbstractThis study assesses the potential impacts of future global warming on the carbon budget of terrestrial ecosystems across monsoon Asia using the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP) dataset. We used simulation results of two emission pathways (RCP2.6 and RCP8.5), climate projections of five climate models, and seven terrestrial biome models to analyze the changes in net primary production and carbon stocks in the South, Southeast, and East Asian subregions during the period 1981–2099. The simulations indicated that by the end of the 21st century, net primary production would increase by 9–45 % and ecosystem carbon storage would increase by 42–86 Pg C. The clearest climatic impacts were found when using the adaptation‐oriented emission scenario (RCP8.5), which assumes a greater CO2 increase and a larger change in climatic conditions. Substantial disparities in temporal trajectories and spatial patterns were found in the estimated changes, owing to the uncertainties in the emission scenarios, climate projections, and ecosystem models. We attempted to derive consistent patterns throughout the simulations to specify potential hotspots of climatic impacts (e.g., soil carbon change in the southern Tibetan Plateau). Finally, we discuss changes to the climatic characteristics in the study region (e.g., a change in the rainy season), the implications for ecosystem services, and the need for collaborative field monitoring studies.

Late Miocene vegetation of the Pannonian Basin

The Pannonian Basin system provides sufficient data to study local and regional vegetation in the context of palaeoclimate and palaeogeography. The present study attempts to make use of the latest results in stratigraphy and track vegetation change throughout the Late Miocene. Vegetation layers are reconstructed for five time slices, from 10.8Ma to 6.5Ma, and placed in a palaeogeographic context. Plant functional types and their distribution, frequently applied in ecological studies and biome modelling, serve as a tool for reconstructing palaeovegetation units. A classification system is introduced considering non-zonal elements as well, in order to represent the Neogene floral record. The PFT spectra obtained from fossil leaf assemblages indicate the presence of mainly broadleaved deciduous vegetation throughout the regarded time span, with variable diversities of conifers and broadleaved evergreen vegetation components. During the Late Miocene, the lowland vegetation of the Pannonian realm seemed to be more homogeneous than reported in other reconstructions, which is in line with the persistence of overall warm and humid climate conditions. The existence of distinctly dry periods as partly suggested by other proxies is not supported. At the same time, data suggest the coeval declining trend of the broadleaved evergreen component in the study area, and its final complete disappearance from the north of the Pannonian Basin. In the younger time slices, constantly humid conditions might have existed along the northern border of the lake, possibly connected to uplift pulses of the Alps and Carpathians.

Impacts of future climate change on the carbon budget of northern high-latitude terrestrial ecosystems: An analysis using ISI-MIP data

This paper assesses future changes in the carbon budgets of northern terrestrial ecosystems (above 60°N) using data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). By analyzing simulations from seven biome models driven by five climate scenarios under two representative concentration pathways (RCP2.6 and RCP8.5), the range of responses and their uncertainty in the 21st century was evaluated. The biome models consistently simulated a gradual increase in vegetation productivity driven by an elevated atmospheric CO2 concentration and a longer growing period. By the 2090s, most simulations showed average net carbon uptake into the northern terrestrial ecosystems of +27 Pg C for RCP2.6 and +48 Pg C for RCP8.5. These estimates showed a wide range of variability among simulations, especially for soil carbon stocks. Even under low greenhouse gas concentrations (RCP2.6), most simulations indicated that vegetation productivity and biomass would change by more than 10%, implying that it will be difficult to completely prevent climatic impacts in northern regions. Simulated spatial patterns and seasonality in the carbon budget can be used to identify sensitive areas and seasons, allowing for improved monitoring. Further research combining observations and modeling will be required to reduce estimation uncertainty and devise ecosystem management options.

A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

Abstract. Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.