Potential Natural Vegetation Distribution Research Articles

Application of the Worldwide Bioclimatic Classification System to determine bioclimatic features and potential natural vegetation distribution in Van Chan district, Vietnam

Application of the Worldwide Bioclimatic Classification System to determine bioclimatic features and potential natural vegetation distribution in Van Chan district, Vietnam

Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system (v2.53)

Abstract. Central to the development of Earth system models (ESMs) has been the coupling of previously separate model types, such as ocean, atmospheric, and vegetation models, to address interactive feedbacks between the system components. A modelling framework which combines a detailed representation of these components, including vegetation and other land surface processes, enables the study of land–atmosphere feedbacks under global climate change. Here we present the initial steps of coupling LPJ-GUESS, a dynamic global vegetation model, to the atmospheric chemistry-enabled atmosphere–ocean general circulation model EMAC. The LPJ-GUESS framework is based on ecophysiological processes, such as photosynthesis; plant and soil respiration; and ecosystem carbon, nitrogen, and water cycling, and it includes a comparatively detailed individual-based representation of resource competition, plant growth, and vegetation dynamics as well as fire disturbance. Although not enabled here, the model framework also includes a crop and managed-land scheme, a representation of arctic methane and permafrost, and a choice of fire models; and hence it represents many important terrestrial biosphere processes and provides a wide range of prognostic trace-gas emissions from vegetation, soil, and fire. We evaluated an online one-way-coupled model configuration (with climate variable being passed from EMAC to LPJ-GUESS but no return information flow) by conducting simulations at three spatial resolutions (T42, T63, and T85). These were compared to an expert-derived map of potential natural vegetation and four global gridded data products: tree cover, biomass, canopy height, and gross primary productivity (GPP). We also applied a post hoc land use correction to account for human land use. The simulations give a good description of the global potential natural vegetation distribution, although there are some regional discrepancies. In particular, at the lower spatial resolutions, a combination of low-temperature and low-radiation biases in the growing season of the EMAC climate at high latitudes causes an underestimation of vegetation extent. Quantification of the agreement with the gridded datasets using the normalised mean error (NME) averaged over all datasets shows that increasing the spatial resolution from T42 to T63 improved the agreement by 10 %, and going from T63 to T85 improved the agreement by a further 4 %. The highest-resolution simulation gave NME scores of 0.63, 0.66, 0.84, and 0.53 for tree cover, biomass, canopy height, and GPP, respectively (after correcting tree cover and biomass for human-caused deforestation which was not present in the simulations). These scores are just 4 % worse on average than an offline LPJ-GUESS simulation using observed climate data and corrected for deforestation by the same method. However, it should be noted that the offline LPJ-GUESS simulation used a higher spatial resolution, which makes the evaluation more rigorous, and that excluding GPP from the datasets (which was anomalously better in the EMAC simulations) gave 10 % worse agreement for the EMAC simulation than the offline simulation. Gross primary productivity was best simulated by the coupled simulations, and canopy height was the worst. Based on this first evaluation, we conclude that the coupled model provides a suitable means to simulate dynamic vegetation processes in EMAC.

Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM).

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present.

Predicting the distribution of potential natural vegetation based on species functional groups in fragmented and species-rich forests

Background and aims – Potential natural vegetation (PNV) can provide a basic reference in guiding the restoration activities for damaged landscapes. Our aim was to find a practicable approach of reconstructing PNV based on functional groups (FGs) in species rich and fragmented forest region. Methods – A total of 149 sample plots (20 × 20 m) were laid and investigated systematically by 1 × 1 km or 1 × 2 km grids across the 482 km 2 forest region in Bawangling nature reserve, Hainan Island, China. The 579 woody plant species found were aggregated into eight functional groups (FGs) according to successional status and potential maximum height. The ecological niche model (MaxEnt) was adopted in predicting the potential distribution of the FGs. The relationship between occurrence probability of FGs and environmental factors was determined as a function of the predicted response curves. The PNV was produced by the overlay of maps for the potential distribution of the FGs, while referring the FGs interactions. Key results – The predicted pioneer FGs scattered widely in the whole landscape, while climax FGs mainly distributed in the central and south part of the study region. Pioneer FGs could better withstand environmental change and occurred in warmer and drier sites, while climax FGs are distributed in cooler and wetter conditions. The PNV could be reconstructed by considering interactions among the FGs. Sixteen main functional patch types were reconstructed in the tropical forest landscape, among which twelve were dominated by climax FGs, accounting for 72.7% of the area, and only four were dominated by pioneer FGs, and accounting for 18.8% of the area. Conclusion – We produced successful prediction of the observed PNV by applying a niche-based model (MaxEnt) based on FGs in fragmented and species rich forest region. This is helpful for predicting how PNV will change to natural and anthropic stressors.

Characteristics of global potential natural vegetation distribution from 1911 to 2000 based on comprehensive sequential classification system approach

AbstractBioclimatology based vegetation classification models play an important role in the response of terrestrial ecosystems to global climate change. In this paper, three periods (1911–1940, 1941–1970 and 1971–2000) of Potential Natural Vegetation (PNV) maps were created based on the CSCS (Comprehensive Sequential Classification System) model and the CRU_TS 2.1 datasets. A model of the mean center was used to calculate the shift distance and direction for each broad vegetation category during the three periods. Results indicate that: (i) the area of tundra and alpine steppe and desert decreased by 5.1 and 5.5%, while the area of forest and grassland increased by 2.3 and 3.8% from 1911 to 2000 at global scale, respectively. However, there was a significant difference in the magnitude of area change in northern and southern hemispheres. And (ii) the tundra and alpine steppe, semi‐desert, savanna, temperate forest and subtropical forest shifted towards the poles; the frigid desert and temperate humid grassland shifted towards the equator, while the warm desert shifted towards southwest, the tropical forest shifted towards southwest in the northern hemisphere and southeast in the southern hemisphere, and the steppe shifted towards northeast in the northern hemisphere and northwest in the southern hemisphere. The shift distance of the warm desert in the southern hemisphere was the largest among the 10 broad vegetation categories.

An objective methodology for potential vegetation reconstruction constrained by climate

Reconstructions of modern Potential Natural Vegetation (PNV) are widely used in climate modelling and vegetation survey as a starting point for studies (historical changes of land-use, past or future vegetation distribution modelling, etc.). A PNV distribution is often related to vegetation models, which are based on empirical relationships between vegetation (or pollen data in paleoecological studies) and climate. Vegetation models are used to directly simulate a PNV distribution or to correct vegetation types derived from remotely-sensed observations in human-impacted regions. Consequently, these methods are quite subjective and include biases from models. This article proposes a new approach to build a high-resolution PNV map using a statistical model.As vegetation is a nominal variable, our method consists in applying a multinomial logistic regression (MLR). MLR build statistical relationships between BIOME 6000 data covering Europe and several climatological variables from the Climate Research Unit (CRU).The PNV reconstructed by MLR appears similar to those reconstructed from remotely-sensed data or simulated by a vegetation model (BIOME 4) except in southern Europe with the establishment of warm-temperate forests. MLR produces a realistic PNV distribution, which is the closest to BIOME 6000 data and provides the vegetation distribution in each grid-cell of our map. Moreover, MLR allows us to compute an uncertainty index that appears as a convenient tool to highlight the regions lacking some data toimprove the PNV distribution. The MLR method does not suffer any dynamic biases or subjective corrections and is a fast and objective alternative to the other methods. MLR provides an independent reference for vegetation models that is entirely based on vegetation and climatological data.

Statistical modelling of a new global potential vegetation distribution

The potential natural vegetation (PNV) distribution is required for several studies in environmental sciences. Most of the available databases are quite subjective or depend on vegetation models. We have built a new high-resolution world-wide PNV map using a objective statistical methodology based on multinomial logistic models. Our method appears as a fast and robust alternative in vegetation modelling, independent of any vegetation model. In comparison with other databases, our method provides a realistic PNV distribution in agreement with respect to BIOME 6000 data. Among several advantages, the use of probabilities allows us to estimate the uncertainty, bringing some confidence in the modelled PNV, or to highlight the regions needing some data to improve the PNV modelling. Despite our PNV map being highly dependent on the distribution of data points, it is easily updatable as soon as additional data are available and provides very useful additional information for further applications.

Exploring pollen percentage threshold values as an indication for the regional presence of major European trees

The aim of this investigation was to delimit pollen percentage threshold values of the major European trees as an indication of regional presence. These values can then be applied to mapping the palaeodistribution of these trees at coarse regional scales. A brief review of the most commonly applied thresholds in the published literature demonstrates the complexity of the problem and the need for this kind of study. Pollen threshold values are proposed for the presence of each of the 20 tree taxa investigated by comparing modern pollen data (2195 samples collected from a network of sites across Europe) with two sources of plant species distribution information: the modified Atlas Florae Europeae (AFE) and the map of potential natural vegetation (PNV). For 17 taxa, the modern samples frequently contain small proportions of its pollen (0.1–0.5%) regardless of the sample location with respect to the species distribution of that taxon. The best agreement between the presence of pollen and the distribution information from both AFE and the PNV map was found for Quercus, Pinus, Picea and Fagus. 12 taxa agree with AFE in as few as 9 or as many as 57% of the samples, depending upon taxon, while 13 taxa agree with the PNV map in as few as 2 or as many as 52% of the samples. Most of the pollen types reflect the AFE distribution of the parent trees better than the PNV distribution. The occurrence of pollen of Fagus, Abies, Picea and Quercus, however, relates to the tree distribution information from the PNV map as well or even better than it does to the AFE information. Based on this dataset we suggest new threshold values that minimise the presence of pollen outside the distribution, without a large reduction of the number of rightly assigned samples. We also emphasise that in heterogeneous data-sets a pollen threshold of 0.5% is a better criterion for regional presence of a tree than the often chosen continuous pollen curve.

Erratum to: Sensitivity of potential natural vegetation in China to projected changes in temperature, precipitation and atmospheric CO2

A sensitivity study was performed to investigate the responses of potential natural vegetation distribution in China to the separate and combined effects of temperature, precipitation and [CO2], using the process-based equilibrium terrestrial biosphere model BIOME4. The model shows a generally good agreement with a map of the potential natural vegetation distribution based on a numerical comparison using the ΔV statistic (ΔV = 0.25). Mean temperature of each month was increased uniformly by 0–5 K, in 0.5- or 1-K intervals. Mean precipitation of each month was increased and decreased uniformly by 0–30%, in 10% intervals. The analyses were run at fixed CO2 concentrations of 360 and 720 ppm. Temperature increases shifted most forest boundaries northward and westward, expanded the distribution of xeric biomes, and confined the tundra to progressively higher elevations. Precipitation increases led to a greater area occupied by mesic biomes at the expense of xeric biomes. Most vegetation types in the temperate regions, and on the Tibetan Plateau, expanded westward into the dry continental interior with increasing precipitation. Precipitation decreases had opposite effects. The modelled effect of CO2 doubling was to partially compensate for the negative effect of drought on the mesic biomes and to increase potential ecosystem carbon storage by about 40%. Warming tended to counteract this effect, by reducing soil carbon storage. Forest biomes showed substantial resilience to climate change, especially when the effects of increasing [CO2] were taken into account. Savannas, dry woodland and tundra biomes proved sensitive to temperature increases. The transition region of grassland and forest, and the Tibetan plateau, was the most vulnerable region.

Sensitivity of potential natural vegetation in China to projected changes in temperature, precipitation and atmospheric CO2

A sensitivity study was performed to investigate the responses of potential natural vegetation distribution in China to the separate and combined effects of temperature, precipitation and [CO2], using the process-based equilibrium terrestrial biosphere model BIOME4. The model shows a generally good agreement with a map of the potential natural vegetation distribution based on a numerical comparison using the ΔV statistic (ΔV = 0.25). Mean temperature of each month was increased uniformly by 0–5 K, in 0.5- or 1-K intervals. Mean precipitation of each month was increased and decreased uniformly by 0–30%, in 10% intervals. The analyses were run at fixed CO2 concentrations of 360 and 720 ppm. Temperature increases shifted most forest boundaries northward and westward, expanded the distribution of xeric biomes, and confined the tundra to progressively higher elevations. Precipitation increases led to a greater area occupied by mesic biomes at the expense of xeric biomes. Most vegetation types in the temperate regions, and on the Tibetan Plateau, expanded westward into the dry continental interior with increasing precipitation. Precipitation decreases had opposite effects. The modelled effect of CO2 doubling was to partially compensate for the negative effect of drought on the mesic biomes and to increase potential ecosystem carbon storage by about 40%. Warming tended to counteract this effect, by reducing soil carbon storage. Forest biomes showed substantial resilience to climate change, especially when the effects of increasing [CO2] were taken into account. Savannas, dry woodland and tundra biomes proved sensitive to temperature increases. The transition region of grassland and forest, and the Tibetan plateau, was the most vulnerable region.

Simple statistical approach for computing land cover types and potential natural vegetation

The main objective of this study was to show the potential of a simple and computationally inexpensive statistical method for the computation of land cover types (LCTs) and potential natural vegetation (PNV), which can be easily adapted to any LCT scheme used by climate models. We propose a diagnostic model (Vegetation Reconstruction by Diagnostic Equilibrium, VERDE), which is based on the cluster analysis of high-resolution datasets of observed LCT distribution and of climate variables. We discuss the reliability of this statistical approach and show that VERDE can be applied for reconstructing PNV distribution in areas such as Europe, India, and China where original vegetation has been replaced by crops and urban areas. According to VERDE, the dominant PNV consists of broadleaf deciduous trees in Central Europe, mixed savanna and grassland in Eastern Europe at mid-latitudes, and evergreen needle trees in Russia. Large areas of India are covered by savanna, and of China by grassland, mixed forest, and evergreen broadleaf trees. VERDE was applied to 5 climate model scenarios (produced by HadCM3, GFDL-CM2.0, IPSL-CM4, CSIRO-MK3, and CNRMCM3) to identify changes in potential vegetation at a global scale that would be induced by the projected climate change at the end of the 21st century. In the Northern Hemisphere, our results showed an increase in barren soils (deserts) in the areas from the tropics to the mid-latitudes, a northward shift of various types of forest, and a reduction in snowor ice-covered land and in areas occupied by shrubs and bushes (tundra) at high latitudes. Changes were smaller in the Southern Hemisphere and suggest increases in savanna in South America and shrublands in Australia.

Potential future changes of the terrestrial ecosystem based on climate projections by eight general circulation models

A number of previous modeling studies have assessed the implications of projected CO2‐induced climate change for future terrestrial ecosystems. However, although current understanding of possible long‐term response of vegetation to elevated CO2 and CO2‐induced climate change in some geographical areas (e.g., the high‐latitude regions) has been strengthened by dint of accumulating evidence from these past studies, it is still weak in others. This study examines the responses of global potential natural vegetation distribution, net primary production (NPP), and fire emissions to future changes in atmospheric CO2 concentration and climate using the National Center for Atmospheric Research Community Land Model's dynamic global vegetation model. The model is run to vegetative equilibrium (i.e., with respect to leaf area index (LAI) and vegetation coverage) driven with preindustrial climate and future climate near 2100, respectively, simulated by eight general circulation models (GCMs). The simulated potential vegetation under the preindustrial control mean climate (CO2 concentration held at 275 ppm) is compared with that under the SRESA1B 2100 mean climate (CO2 concentration stabilizes at 720 ppm beyond 2100). Simulated vegetation response ranges from mild changes of the fractional coverage of different plant functional types to the rather dramatic changes of dominant plant functional types. Although such response differs significantly across different GCM climate projections, a quite consistent spatial pattern emerges, characterized by a considerable poleward spread or shift of temperate and boreal forests in the Northern Hemisphere high latitudes, and a substantial degradation of vegetation type in the tropics (e.g., increase of drought deciduous trees coverage at the expense of evergreen trees) especially in portions of West and southern Africa and South America. Despite the widespread degradation of vegetation type in the tropics, NPP, and growing season LAI are predicted to increase under most GCM scenarios over most of the globe. Carbon fluxes to the atmosphere due to fire generally increase too across the globe. Such responses of NPP and fire occurrence result from the synergistic effects of CO2 concentration changes, climate changes, and vegetation changes. In the HadCM‐driven simulation, however, extreme responses are shown in some regions: Deciduous forest is replaced by grasses in large areas in the middle latitudes, and substantial areas in northern South America and southern Africa predominantly covered by evergreen forest are replaced with grasses while NPP and fire emissions reduce drastically (by more than 100%). A future paper will examine how the biosphere response documented here influences the impact of climate change on surface hydrological conditions.

Ecosystem classification for EU habitat distribution assessment in sandy coastal environments: An application in central Italy

Many recent developments in coastal science have gone against the demands of European Union legislation. Coastal dune systems which cover small areas of the earth can host a high level of biodiversity. However, human pressure on coastal zones around the world has increased dramatically in the last 50 years. In addition to direct habitat loss, the rapid extinction of many species that are unique to these systems can be attributed to landscape deterioration through the lack of appropriate management. In this paper, we propose to use of an ecosystem classification technique that integrates potential natural vegetation distribution as a reference framework for coastal dune EU Habitats (92/43) distribution analysis and assessment. As an example, the present study analyses the EU Habitats distribution within a hierarchical ecosystem classification of the coastal dune systems of central Italy. In total, 24 land elements belonging to 8 land units, 5 land facets, 2 land systems and 2 land regions were identified for the coastal dunes of central Italy, based on diagnostic land attributes. In central Italy, coastal dune environments including all the beach area, mobile dunes and all the fixed-dune land elements contain or could potentially hold at least one EU habitat of interest. Almost all dune slack transitions present the potentiality for the spontaneous development of EU woodlands of interest. The precise information concerning these ecosystems distribution and ecological relationships that this method produces, makes it very effective in Natura 2000 European network assessment. This hierarchical ecosystem classification method facilitates the identification of areas to be surveyed and eventually bound, under the implementation of EU Habitat directive (92/43) including areas with highly disturbed coastal dune ecosystems.

Effects of recent climate trends on the distribution of potential natural vegetation in Central Germany

Introducing climate quotients for the growing season (Q(gs)) provides a way to quantify effects of climate trends with respect to Potential Natural Vegetation (PNV), especially beech forests (Fagus sylvatica L.) in Central Germany. What is crucial in this regard is the great influence of the dominant decrease in the amount of precipitation (up to 40% in the last 50 years) during the growing season versus the dormant season. However, precipitation during the dormant season (which is predominantly increasing: up to 40% in the last 50 years) is also important for replenishing the soil water supply. The Q(gs) values of the Climatic Normal period of 1971-2000 are generally higher (up to 12% in lowland areas) compared with the Climatic Normal period of 1961-1990, the extent of the difference being in general inversely proportional to elevation above sea level. What this means for the area under investigation is that humidity conditions, which generally improve as the elevation above sea level increases, have a positive effect on the site potential. However, a comparison of the climatologically important period of 1991-2003 with the period of 1961-1990 (area-wide increase between 12% and 16%) could not identify this positive effect of elevation on precipitation for the area under investigation. With regard to the recent climate-based trends of PNV, we have shown that all natural spatial units in Central Germany are affected by progressing continentality (i.e., dryness) during the growing season and the resulting deterioration of the site potential. The area of potential beech forest at lower elevation has decreased in favour of oak forest as PNV, while less change is observed in the montane area.

Primi risultati per una nuova regionalizzazione fitogeografia del territorio italiano

Biogeographia vol. XXVIII - 2007 (Pubb/icato il 30 dicembre 2007) Biogeografia de/I’Appennino eentra/e e sertentrionale: trenfanni dopo Primi risultati per una nuova regionalizzazione fitogeografica del territorio italiano CARLO BLASI, GOFFREDO FILIBECK*, SABINA BURRASCANO, RICCARDO COPIZ**, ROMEO DI PIETRO°, STEFAN IA ERCOLE, EDDA LATTANZI, LEONARDO ROSATI, AGNESE TILIA Dzpartimento di Bio/agizz Vegerzzle, Uniuersitiz di Roma qLa Szzpienzzz’: pizzzzzzle Aldo Mom 5, 00185 Roma (Italy); e-mzzil: czzrlo.b/zzsi@zmiromzz1.it *Dipzzrtimmt0 DEC 05, Universitfz de/[zz Tzzscizz, largo Universifiz, 01100 Viterbo {ftzz/y) **Dz'pzzrtz'mem‘0 S T A T, U7zz'z/ersiziz de[ M olise, contrzzdzz Fonte Lzzppone, 86190 P656‘/:76’, Isemizz (ltzzly) °Dz'pzzrtimem‘0 I TAC/‘1, Uiziuersitfz di Roma “La Szzpienzzz”, z/itz Flzzmirzitz 7 8, 00196 Roma (ftzzey) Key words: biogeographical regions, local fioras, potential natural vegetation, phytogeography, regionalization SUMMARY Biogeographical regionalization should not be confused with ecological cartography or landscape classification, as biogeographical classification should be based only on species distribution. Therefore, the optimal data set for a phytogeographical (fioristic) Classification of Italy would be a floristic atlas including all the vascular plants species of the country: grid cells should be treated as OGUS (Operational Geographic Unit) and elaborated through multivariate presence/ absence analysis. However, such an atlas has never been realized in our country. Aim of the paper is to present a quantitative phytogeographical classification of Italy based on available data, i.e. the new chet:l(—list of the Italian vascular Hora, the large amount ofpublished local Horas and information about the distribution of Potential Natural Vegetation (vegetation series). As the check-list shows the plant list of each of the 20 administrative regions of Italy, these can be treated as OGUS For a first, coarse—grain framework classification of the country. A more detailed and fine—grainecl analysis of Italy’s phytogeographical units can be made analyzing a wide set oflocal floras, chosen — among the many available — on the basis of their study area surface and ecological heterogeneity. We also present a detailed analysis regarding the chorological attributes of species exclusive of the Thyrrenic regions compared to the Adriatic ones. The complex of the analysis confirm the presence of a gradient north—south and a clear separation est—west along the Peninsula. Results confirm that the adopted method is a valuable approach and propose a new boundary for the Centre— European Region in Southern Italy. q INTRODUZIONE La distribuzione degli organismi dipende da fattori ecologici, cioe dalle catat- tetistiche dell’arnbiente e dalle interazioni fra organismi e comunita, e da fat-

Development of the Bio-Geographical and GeoChemical (BGGC) Model for Assessments of Climate Change Impacts on the Terrestrial Ecosystem in Japan

This study developed the Bio-Geographical and GeoChemical model (BGGC model) to assess the future impacts of global climate change, as prescribed by the IPCC-SRES, on the distribution and functioning of terrestrial ecosystems in Japan. The BGGC model simulates the cycling of carbon, nitrogen, and water in vegetation, soil ecosystems and the atmosphere. Some modules in the model borrow most of their basic structures from the sub-model of CENTURY4 (Parton et al., 1993) and the modified BIOME3 (Ishigami et al., 2002). The BGGC model is broadly divided into two sub-models, the vegetation competition sub-model and the soil organic matter sub-model. The vegetation competition sub-model consists of the photosynthesis model and the canopy model. The photosynthesis model estimates the optimized net primary productivity (NPP) and leaf area index (LAI) to satisfy the soil nitrogen, and annual moisture. The canopy model considers the canopy structure for forest vegetation types. On the other hand, the soil organic matter sub-model, which is linked to the vegetation competition sub-model, simulates carbon, nitrogen, and water dynamics in the soil ecosystem. The distribution of potential natural vegetation types was determined by the estimated NPP and LAI. In order to assess the impact of climate change on the terrestrial ecosystem, this study estimated the distribution of potential natural vegetation in Japan using NPP. The GCMs experimental data used were the CSIRO-Mk2 and ECHAM4/OPYC3 for each of A2 and B2 scenarios in the SRES. Comparison of the averages of simulated NPP under each scenario with the average NPP under current climate conditions showed that the average NPP could increase about 19 to 33 percent by the year 2050 and 25 to 53 percent by the year 2080.

日本の潜在的な自然植生分布に対する気候変化の影響予測

In a previous paper, we modified some sub-models of BIOME3 to be applied to 1×1 km mesh data in order to increase the accuracy of simulation.Using this modified model, we estimated potential natural vegetation distribution under climatic change using 4 types of GCM experiment data. GCM data that can be used presently have rough spatial resolution, so it is difficult to estimate the effect of climatic change at a local scale. Therefore, we used GCM data around Japan that was interpolated to a 10×10 km mesh.We calculated the NPP, and predicted the distribution of potential natural vegetation and its vulnerability for the 2020s, 2050s and 2080s. Results from the simulation indicated the possibility of 60-100% increase of NPP in the 2080s. The increase in NPP was explained by the increase in air temperature and the concentration of CO2. Potential natural vegetation in Japan would be affected over a wide area by climatic change. In particular, the alpine plants/subalpine conifer forest area would decrease. In mixed forest in the Hokkaido area, where broad-leaved deciduous trees and conifer trees coexist, broad-leaved deciduous trees would become dominant. Broad-leaved evergreen forest area would expand, and the subtropical forest would to a prior species along the coastline of western Japan.

Количественная оценка отклонения ландшафтного разнообразия от потенциальной естественной растительности при помощи энтропии Шеннона

In the past 20 years, several metrics have been developed to quantify various aspects of landscape structure and diversity in space and time, and most have been tested on grid- based thematic maps. Once landscape patterns have been quantified, their effects on ecological functions can be explained if the expected pattern in the absence of specific processes is known. This type of expected pattern has been termed a neutral landscape model. In the landscape-ecological literature, researchers traditionally adopt random and fractal computer-generated neutral landscape models to verify the expected relationship between a given ecological process and landscape spatial heterogeneity. Conversely, little attention has been devoted to distribution patterns of potential natural vegetation (PNV) as an ecological baseline for the evaluation of pattern-process interactions at the landscape scale. As an application for demonstration, we propose a neutral model based on PNV as a possible reference for a quantitative comparison with actual vegetation (ARV) distribution. Within this context, we introduce an evenness-like index termed "actual-to-potential entropy ratio’ (HA/P=HARV/HPNV, where H is Shannon’s entropy). Results show that, despite the hypothetical character of most PNV maps, the use of PNV distribution as a baseline for a quantitative comparison with ARV distribution may represent a first step towards г general model for the evaluation of the effects of disturbance on vegetation patterns and diversity.

Quantitative comparison of the diversity of landscapes with actual vs. potential natural vegetation

Abstract. In the past 20 years, several metrics have been developed to quantify various aspects of landscape structure and diversity in space and time, and most have been tested on grid‐based thematic maps. Once landscape patterns have been quantified, their effects on ecological functions can be explained if the expected pattern in the absence of specific processes is known. This type of expected pattern has been termed a neutral landscape model. In the landscape‐ecological literature, researchers traditionally adopt random and fractal computer‐generated neutral landscape models to verify the expected relationship between a given ecological process and landscape spatial heterogeneity. Conversely, little attention has been devoted to distribution patterns of potential natural vegetation (PNV) as an ecological baseline for the evaluation of pattern‐process interactions at the landscape scale. As an application for demonstration, we propose a neutral model based on PNV as a possible reference for a quantitative comparison with actual vegetation (AC V) distribution. Within this context, we introduce an evenness‐like index termed ‘actual‐to‐potential entropy ratio’ (HA/P = HACV/HPNV, where H is Shannon's entropy). Results show that, despite the hypothetical character of most PNV maps, the use of PNV distribution as a baseline for a quantitative comparison with ACV distribution may represent a first step towards a general model for the evaluation of the effects of disturbance on vegetation patterns and diversity.

BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types

The equilibrium terrestrial biosphere model BIOME3 simulates vegetation distribution and biogeochemistry, and couples vegetation distribution directly to biogeochemistry. Model inputs consist of latitude, soil texture class, and monthly climate (temperature, precipitation, and sunshine) data on a 0.5° grid. Ecophysiological constraints determine which plant functional types (PFTs) may potentially occur. A coupled carbon and water flux model is then used to calculate, for each PFT, the leaf area index (LAI) that maximizes net primary production (NPP), subject to the constraint that NPP must be sufficient to maintain this LAI. Competition between PFTs is simulated by using the optimal NPP of each PFT as an index of competitiveness, with additional rules to approximate the dynamic equilibrium between natural disturbance and succession driven by light competition. Model output consists of a quantitative vegetation state description in terms of the dominant PFT, secondary PFTs present, and the total LAI and NPP for the ecosystem. Canopy conductance is treated as a function of the calculated optimal photosynthetic rate and water stress. Regional evapotranspiration is calculated as a function of canopy conductance, equilibrium evapotranspiration rate, and soil moisture using a simple planetary boundary layer parameterization. This scheme results in a two‐way coupling of the carbon and water fluxes through canopy conductance, allowing simulation of the response of photosynthesis, stomatal conductance, and leaf area to environmental factors including atmospheric CO2. Comparison with the mapped distribution of global vegetation shows that the model successfully reproduces the broad‐scale patterns in potential natural vegetation distribution. Comparison with NPP measurements, and with an FPAR (fractional absorbed photosynthetically active radiation) climatology based on remotely sensed greenness measurements, provides further checks on the model's internal logic. The model is envisaged as a tool for integrated analysis of the impacts of changes in climate and CO2 on ecosystem structure and function.