A biome classification of China based on plant functional types and the BIOME3 model

A biome classification for China was established based on plant functional types (PFTs) using the BIOME3 model to include 16 biomes. In the eastern part of China, the PFTs of trees determine mostly the physiognomy of landscape. Biomes range from boreal deciduous coniferous forest/woodland, boreal mixed forest/woodland, temperate mixed forest, temperate broad-leaved deciduous forest, warm-temperate broad-leaved evergreen/mixed forest, warm-temperate/cool-temperate evergreen coniferous forest, xeric woodland/scrub, to tropical seasonal and rain forest, and tropical deciduous forest from north to south. In the northern and western part of China, grass is the dominant PFT. From northeast to west and southwest the biomes range from moist savannas, tall grassland, short grassland, dry savannas, arid shrubland/steppe, desert, to alpine tundra/ice/polar desert. Comparisons between the classification introduced here and the four classifications which were established over the past two decades, i.e. the vegetation classification, the vegetation division, the physical ecoregion, and the initial biome classification have showed that the different aims of biome classifications have resulted in different biome schemes each with its own unique characteristics and disadvantages for global change study. The new biome classification relies not only on climatic variables, but also on soil factor, vegetation functional variables, ecophysiological parameters and competition among the PFTs. It is a comprehensive classification that using multivariables better expresses the vegetation distribution and can be compared with world biome classifications. It can be easily used in the response study of Chinese biomes to global change, regionally and globally.     

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.     

Global distribution and bioclimatic characterization of alpine biomes

Although there is a general consensus on the distribution and ecological features of terrestrial biomes, the allocation of alpine ecosystems in the global biogeographic system is still unclear. Here, we delineate a global map of alpine areas above the treeline by modelling regional treeline elevation at 30 m resolution, using global forest cover data and quantile regression. We then used global datasets to 1) assess the climatic characteristics of alpine ecosystems using principal component analysis, 2) define bioclimatic groups by an optimized cluster analysis and 3) evaluate patterns of primary productivity based on the normalized difference vegetation index. As defined here, alpine biomes cover 3.56 Mkm² or 2.64% of land outside Antarctica. Despite temperature differences across latitude, these ecosystems converge below a sharp threshold of 5.9°C and towards the colder end of the global climatic space. Below that temperature threshold, alpine ecosystems are influenced by a latitudinal gradient of mean annual temperature and they are climatically differentiated by seasonality and continentality. This gradient delineates a climatic envelope of global alpine biomes around temperate, boreal and tundra biomes as defined in Whittaker's scheme. Although alpine biomes are similarly dominated by poorly vegetated areas, world ecoregions show strong differences in the productivity of their alpine belt irrespectively of major climate zones. These results suggest that vegetation structure and function of alpine ecosystems are driven by regional and local contingencies in addition to macroclimatic factors.     

Phenological description of natural vegetation in southern Africa using remotely‐sensed vegetation data

Abstract. Various attempts have been made to describe and map the vegetation of southern Africa with recent efforts having an increasingly ecologi cal context. Vegetation classification is usually based on vegetation physiognomy and floristic composition, but phenology is useful source of information which is rarely used, although it can contribute functional information on ecosystems. The objectives of this study were to identify a suite of variables derived from time‐series NDVI data that best describe the phenological phenomena of vegetation in southern Africa and, secondly, to assess a classification of pixels of the study area based on NDVI variables using a preexisting map of the biomes that was delimited on the basis of life forms and climate. A number of variables were derived from the satellite data for describing phenological phenomena, which were analysed by multivariate techniques to determine which variables best explained the variation in the satellite data. This set of variables was used to produce a phenological classification of the vegetation of southern Africa, the results of which are discussed in relation to their concordance with the existing biome boundaries.     

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

Questions: What are the patterns of remotely sensed vegetation phenology, including their inter‐annual variability, across South Africa? What are the phenological attributes that contribute most to distinguishing the different biomes? How well can the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Location: South Africa. Method: Ten‐day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing season and estimates of productivity, based on small and large integral (SI, LI) of NDVI curve, were extracted and long‐term means calculated. A random forest regression tree was run using the metrics as the input variables and the biomes as the dependent variable. A map of the predicted biomes was reproduced and the differentiating importance of each metric assessed. Results: The phenology metrics (e.g. start of growing season) showed a clear relationship with the seasonality of rainfall, i.e. winter and summer growing seasons. The distribution of the productivity metrics, LI and SI were significantly correlated with mean annual precipitation. The regression tree initially split the biomes based on vegetation production and then by the seasonality of growth. A regression tree was used to produce a predicted biome map with a high level of accuracy (73%). Main conclusion: Regression tree analysis based on remotely sensed metrics performed as good as, or better than, previous climate‐based predictors of biome distribution. The results confirm that the remotely sensed metrics capture sufficient functional diversity to classify and map biome level vegetation patterns and function.     

High ecosystem stability of evergreen broadleaf forests under severe droughts

Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non‐evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long‐term Standardized Precipitation and Evaporation Index (SPEI) data and satellite‐derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre‐drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: ?0.08 to ?1.80), area (areal fraction range: 2%–19%), and duration (month range: 7.9–9.1) in the EBF biome over 2000–2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more‐intense climate extremes in the future.     

Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change

Aim Climate change threatens to shift vegetation, disrupting ecosystems and damaging human well‐being. Field observations in boreal, temperate and tropical ecosystems have detected biome changes in the 20th century, yet a lack of spatial data on vulnerability hinders organizations that manage natural resources from identifying priority areas for adaptation measures. We explore potential methods to identify areas vulnerable to vegetation shifts and potential refugia. Location Global vegetation biomes. Methods We examined nine combinations of three sets of potential indicators of the vulnerability of ecosystems to biome change: (1) observed changes of 20th‐century climate, (2) projected 21st‐century vegetation changes using the MC1 dynamic global vegetation model under three Intergovernmental Panel on Climate Change (IPCC) emissions scenarios, and (3) overlap of results from (1) and (2). Estimating probability density functions for climate observations and confidence levels for vegetation projections, we classified areas into vulnerability classes based on IPCC treatment of uncertainty. Results One‐tenth to one‐half of global land may be highly (confidence 0.80–0.95) to very highly (confidence ≥ 0.95) vulnerable. Temperate mixed forest, boreal conifer and tundra and alpine biomes show the highest vulnerability, often due to potential changes in wildfire. Tropical evergreen broadleaf forest and desert biomes show the lowest vulnerability. Main conclusions Spatial analyses of observed climate and projected vegetation indicate widespread vulnerability of ecosystems to biome change. A mismatch between vulnerability patterns and the geographic priorities of natural resource organizations suggests the need to adapt management plans. Approximately a billion people live in the areas classified as vulnerable.     

Global synthesis of leaf area index observations: implications for ecological and remote sensing studies

Aim We present the first global synthesis of plant canopy leaf area index (LAI) measurements from more than 1000 published estimates representing ～400 unique field sites. LAI is a key variable for regional and global models of biosphere‐atmosphere exchanges of energy, carbon dioxide, water vapour, and other materials. Location The location is global, geographically distributed. Results Biomes with LAI values well represented in the literature included croplands, forests and plantations. Biomes not well represented were deserts, shrublands, tundra and wetlands. Nearly 40% of the records in the database were published in the past 10 years (1991–2000), with a further 20% collected between 1981 and 1990. Mean (± SD) LAI, distributed between 15 biome classes, ranged from 1.3 ± 0.9 for deserts to 8.7 ± 4.3 for tree plantations, with temperate evergreen forests (needleleaf and broadleaf) displaying the highest average LAI (5.1–6.7) among the natural terrestrial vegetation classes. Following a statistical outlier analysis, the global mean (± SD) LAI decreased from 5.2 (4.1) to 4.5 (2.5), with a maximum LAI of 18. Biomes with the highest LAI values were plantations > temperate evergreen forests > wetlands. Those with the lowest LAI values were deserts < grasslands < tundra. Mean LAI values for all biomes did not differ statistically by the methodology employed. Direct and indirect measurement approaches produced similar LAI results. Mean LAI values for all biomes combined decreased significantly in the 1990s, a period of substantially more studies and improved methodologies. Main conclusions Applications of the LAI database span a wide range of ecological, biogeochemical, physical, and climate research areas. The data provide input to terrestrial ecosystem and land‐surface models, for evaluation of global remote sensing products, for comparisons to field studies, and other applications. Example uses of the database for global plant productivity, fractional energy absorption, and remote sensing studies are highlighted.     

Implementation of a hierarchical global vegetation classification in ecosystem function models

Abstract. We propose an alternative approach for the currently used biogeographic global vegetation classifications. A hierarchical vegetation classification system is proposed for consistent and routine monitoring of global vegetation. Global vegetation is first defined into six classes based on plant canopy structure and dynamics observable by remote sensing from satellites. Additional biome variability is then represented through a remote sensing derived leaf area index map, and direct climate data sets driving an ecosystem model to compute and map net primary production and evapotranspiration. Simulation results from an ecosystem function model suggest that the six canopy structure-based classes are sufficient to represent global variability in these parameters, provided the spatio-temporal variations in Leaf Area Index and climate are characterized accurately. If a bioclimatically based classification is needed for other purposes, our six class approach can be expanded to a possible 21 classes using archived climatic zones. For example, tropical, subtropical, temperate and boreal labels are defined by absolute minimum temperature. Further separation in each class is possible through changes in water availability defined by precipitation and/or soils. The resulting vegetation classes correspond to many of the existing, conventional global vegetation schemes, yet retain the measure of actual vegetation possible because remote sensing first defines the six biome classes in our classification. Vegetation classifications are no longer an end product but a source of initializing data for global ecosystem function models. Remote sensing with biosphere models directly calculates the ecological functions previously inferred from vegetation classifications, but with higher spatial and temporal accuracy.     

Biome reconstruction from pollen and plant macrofossil data for Africa and the Arabian peninsula at 0 and 6000 years

Biome reconstruction from pollen and plant macrofossil data provides an objective method to reconstruct past vegetation. Biomes for Africa and the Arabian peninsula have been mapped for 6000 years bp and provide a new standard for the evaluation of simulated palaeovegetation distributions. A test using modern pollen data shows the robustness of the biomization method, which is able to predict the major vegetation types with a high confidence level. The application of the procedure to the 6000 years data set (pollen and plant macrofossil analyses) shows systematic differences from the present that are consistent with the numerous previous regional and continental interpretations, while providing a more extensive and more objective basis for such interpretations. Madagascar, eastern, southern and central Africa show only minor changes in terms of biomes, compared to present. Major changes in biome distributions occur north of 15°N, with steppe in many low-elevation sites that are now desert, and temperate xerophytic woods/scrub and warm mixed forest in the Saharan mountains. These shifts in biome distributions imply significant changes in climate, especially precipitation, between 6000 years and present, reflecting a change in monsoon extent combined with a southward expansion of Mediterranean influence.     

Plant biomes demonstrate that landscape resilience today is the lowest it has been since end‐Pleistocene megafaunal extinctions

Resilient landscapes have helped maintain terrestrial biodiversity during periods of climatic and environmental change. Identifying the tempo and mode of landscape transitions and the drivers of landscape resilience is critical to maintaining natural systems and preserving biodiversity given today's rapid climate and land use changes. However, resilient landscapes are difficult to recognize on short time scales, as perturbations are challenging to quantify and ecosystem transitions are rare. Here we analyze two components of North American landscape resilience over 20,000 years: residence time and recovery time. To evaluate landscape dynamics, we use plant biomes, preserved in the fossil pollen record, to examine how long a biome type persists at a given site (residence time) and how long it takes for the biome at that site to reestablish following a transition (recovery time). Biomes have a median residence time of only 230–460 years. Only 64% of biomes recover their original biome type, but recovery time is 140–290 years. Temperatures changing faster than 0.5°C per 500 years result in much reduced residence times. Following a transition, biodiverse biomes reestablish more quickly. Landscape resilience varies through time. Notably, short residence times and long recovery times directly preceded the end‐Pleistocene megafauna extinction, resulting in regional destabilization, and combining with more proximal human impacts to deliver a one‐two punch to megafauna species. Our work indicates that landscapes today are once again exhibiting low resilience, foreboding potential extinctions to come. Conservation strategies focused on improving both landscape and ecosystem resilience by increasing local connectivity and targeting regions with high richness and diverse landforms can mitigate these extinction risks.     

Modern pollen-based biome reconstructions in East Africa expanded to southern Tanzania

New detailed biome reconstructions are proposed in East Africa from modern pollen data derived from 150 sites located in northern Kenya (40 sites), north-western Uganda (51 sites) and southern Tanzania (59 new sites presented as pollen diagram), which are representative of the major vegetation associations occurring in seven phytogeographical regions, mosaics or centres of endemism. We use the standard biomisation method previously published for the African continent, but we reconsider the taxa assignment to plant functional types. We include in this approach all identified taxa (408) except aquatics, ferns and exotic taxa. The method is validated by comparison with local vegetation data and we show that 124 (82.6%) sites are assigned to the correct biome and that for all the biomes under investigation, the number of correct assignments always exceeds the number of incorrect ones. When an incorrect biome reconstruction occurs, mainly toward drier biomes, this is generally linked to the local open/degraded structure of the original vegetation or to the occurrence of a mosaic of open/closed vegetation. In turn, most of the reconstructions of more humid/closed biomes than the corresponding local vegetation (8.6%) remain unexplained. A comparison of our reconstructed biomes with the main East African vegetation types of White's map indicates that 121 (80.6%) sites are assigned to the correct biomes. However, the majority of sites are incorrectly reconstructed compared to Olson and IGBP maps from satellite data, mainly due to incorrect allocation of the land cover classes compared to the potential vegetation. The application of this method to our pollen data set demonstrates that modern pollen assemblages can successfully reconstruct the main modern East African vegetation types.     

Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3

1 We model the potential vegetation and annual net primary production (NPP) of China on a 10′ grid under the present climate using the processed‐based equilibrium terrestrial biosphere model BIOME3. The simulated distribution of the vegetation was in general in good agreement with the potential natural vegetation based on a numerical comparison between the two maps using the ΔV statistic (ΔV = 0.23). Predicted and measured NPP were also similar, especially in terms of biome‐averages. 2 A coupled ocean–atmosphere general circulation model including sulphate aerosols was used to drive a double greenhouse gas scenario for 2070–2099. Simulated vegetation maps from two different CO₂ scenarios (340 and 500 p.p.m.v.) were compared to the baseline biome map using ΔV. Climate change alone produced a large reduction in desert, alpine tundra and ice/polar desert, and a general pole‐ward shift of the boreal, temperate deciduous, warm–temperate evergreen and tropical forest belts, a decline in boreal deciduous forest and the appearance of tropical deciduous forest. The inclusion of CO₂ physiological effects led to a marked decrease in moist savannas and desert, a general decrease for grasslands and steppe, and disappearance of xeric woodland/scrub. Temperate deciduous broadleaved forest, however, shifted north to occupy nearly half the area of previously temperate mixed forest. 3 The impact of climate change and increasing CO₂ is not only on biogeography, but also on potential NPP. The NPP values for most of the biomes in the scenarios with CO₂ set at 340 p.p.m.v. and 500 p.p.m.v. are greater than those under the current climate, except for the temperate deciduous forest, temperate evergreen broadleaved forest, tropical rain forest, tropical seasonal forest, and xeric woodland/scrub biomes. Total vegetation and total carbon is simulated to increase significantly in the future climate scenario, both with and without the CO₂ direct physiological effect. 4 Our results show that the global process‐based equilibrium terrestrial biosphere model BIOME3 can be used successfully at a regional scale.     

Productivity, organism size, and the trophic structure of the major terrestrial biomes

I present a hypothesis suggesting that terrestrial biomes' productivity determines the size of the major organisms and plant physiognomy in them and consequently determines their trophic structure. I suggest a more comprehensive set of patterns over current hypotheses, which consider productivity alone. Based on my hypothesis, I predict that the number of trophic levels decreases with increasing productivity from four in hot deserts to two in productive grasslands and that there are three to four trophic levels in all types of forested biomes. I also suggest that productivity is the limiting factor for the number of trophic levels at the lower end of the terrestrial productivity gradient, herbivore size is the limiting factor at intermediate productivities, and plant physiognomy is the limiting factor in the high productivity range. This contradicts existing hypotheses that predict either an increase (Am Nat 118:240–261, 1981; Am Nat 155:703–723, 2000) or no change (Am Nat 142:379–411, 1993) in the number of trophic levels with the increase in biome productivity.     

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.     

The carbon balance of tropical, temperate and boreal forests

Forest biomes are major reserves for terrestrial carbon, and major components of global primary productivity. The carbon balance of forests is determined by a number of component processes of carbon acquisition and carbon loss, and a small shift in the magnitude of these processes would have a large impact on the global carbon cycle. In this paper, we discuss the climatic influences on the carbon dynamics of boreal, temperate and tropical forests by presenting a new synthesis of micrometeorological, ecophysiological and forestry data, concentrating on three case-study sites. Historical changes in the carbon balance of each biome are also reviewed, and the evidence for a carbon sink in each forest biome and its likely behaviour under future global change are discussed. We conclude that there have been significant advances in determining the carbon balance of forests, but there are still critical uncertainties remaining, particularly in the behaviour of soil carbon stocks.     

Disturbance maintains alternative biome states

Understanding the mechanisms controlling the distribution of biomes remains a challenge. Although tropical biome distribution has traditionally been explained by climate and soil, contrasting vegetation types often occur as mosaics with sharp boundaries under very similar environmental conditions. While evidence suggests that these biomes are alternative states, empirical broad‐scale support to this hypothesis is still lacking. Using community‐level field data and a novel resource‐niche overlap approach, we show that, for a wide range of environmental conditions, fire feedbacks maintain savannas and forests as alternative biome states in both the Neotropics and the Afrotropics. In addition, wooded grasslands and savannas occurred as alternative grassy states in the Afrotropics, depending on the relative importance of fire and herbivory feedbacks. These results are consistent with landscape scale evidence and suggest that disturbance is a general factor driving and maintaining alternative biome states and vegetation mosaics in the tropics.     

Anthropogenic transformation of the biomes, 1700 to 2000

Aim To map and characterize anthropogenic transformation of the terrestrial biosphere before and during the Industrial Revolution, from 1700 to 2000. Location Global. Methods Anthropogenic biomes (anthromes) were mapped for 1700, 1800, 1900 and 2000 using a rule‐based anthrome classification model applied to gridded global data for human population density and land use. Anthropogenic transformation of terrestrial biomes was then characterized by map comparisons at century intervals. Results In 1700, nearly half of the terrestrial biosphere was wild, without human settlements or substantial land use. Most of the remainder was in a seminatural state (45%) having only minor use for agriculture and settlements. By 2000, the opposite was true, with the majority of the biosphere in agricultural and settled anthromes, less than 20% seminatural and only a quarter left wild. Anthropogenic transformation of the biosphere during the Industrial Revolution resulted about equally from land‐use expansion into wildlands and intensification of land use within seminatural anthromes. Transformation pathways differed strongly between biomes and regions, with some remaining mostly wild but with the majority almost completely transformed into rangelands, croplands and villages. In the process of transforming almost 39% of earth's total ice‐free surface into agricultural land and settlements, an additional 37% of global land without such use has become embedded within agricultural and settled anthromes. Main conclusions Between 1700 and 2000, the terrestrial biosphere made the critical transition from mostly wild to mostly anthropogenic, passing the 50% mark early in the 20th century. At present, and ever more in the future, the form and process of terrestrial ecosystems in most biomes will be predominantly anthropogenic, the product of land use and other direct human interactions with ecosystems. Ecological research and conservation efforts in all but a few biomes would benefit from a primary focus on the novel remnant, recovering and managed ecosystems embedded within used lands.     

The role of climate and plant functional trade‐offs in shaping global biome and biodiversity patterns

Aim Two of the oldest observations in plant geography are the increase in plant diversity from the poles towards the tropics and the global geographic distribution of vegetation physiognomy (biomes). The objective of this paper is to use a process‐based vegetation model to evaluate the relationship between modelled and observed global patterns of plant diversity and the geographic distribution of biomes. Location The global terrestrial biosphere. Methods We implemented and tested a novel vegetation model aimed at identifying strategies that enable plants to grow and reproduce within particular climatic conditions across the globe. Our model simulates plant survival according to the fundamental ecophysiological processes of water uptake, photosynthesis, reproduction and phenology. We evaluated the survival of an ensemble of 10,000 plant growth strategies across the range of global climatic conditions. For the simulated regional plant assemblages we quantified functional richness, functional diversity and functional identity. Results A strong relationship was found (correlation coefficient of 0.75) between the modelled and the observed plant diversity. Our approach demonstrates that plant functional dissimilarity increases and then saturates with increasing plant diversity. Six of the major Earth biomes were reproduced by clustering grid cells according to their functional identity (mean functional traits of a regional plant assemblage). These biome clusters were in fair agreement with two other global vegetation schemes: a satellite image classification and a biogeography model (kappa statistics around 0.4). Main conclusions Our model reproduces the observed global patterns of plant diversity and vegetation physiognomy from the number and identity of simulated plant growth strategies. These plant growth strategies emerge from the first principles of climatic constraints and plant functional trade‐offs. Our study makes important contributions to furthering the understanding of how climate affects patterns of plant diversity and vegetation physiognomy from a process‐based rather than a phenomenological perspective.