Distribution Of Functional Types Research Articles

Regional adaptation of a dynamic global vegetation model using a remote sensing data derived land cover map of Russia

The dynamic global vegetation model (DGVM) SEVER has been regionally adapted using a remote sensing data-derived land cover map in order to improve the reconstruction conformity of the distribution of vegetation functional types over Russia. The SEVER model was modified to address noticeable divergences between modelling results and the land cover map. The model modification included a light competition method elaboration and the introduction of a tundra class into the model. The rigorous optimisation of key model parameters was performed using a two-step procedure. First, an approximate global optimum was found using the efficient global optimisation (EGO) algorithm, and afterwards a local search in the vicinity of the approximate optimum was performed using the quasi-Newton algorithm BFGS. The regionally adapted model shows a significant improvement of the vegetation distribution reconstruction over Russia with better matching with the satellite-derived land cover map, which was confirmed by both a visual comparison and a formal conformity criterion.

Prediction of Macronutrients at the Canopy Level Using Spaceborne Imaging Spectroscopy and LiDAR Data in a Mixedwood Boreal Forest

Information on foliar macronutrients is required in order to understand plant physiological and ecosystem processes such as photosynthesis, nutrient cycling, respiration and cell wall formation. The ability to measure, model and map foliar macronutrients (nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg)) at the forest canopy level provides information on the spatial patterns of ecosystem processes (e.g., carbon exchange) and provides insight on forest condition and stress. Imaging spectroscopy (IS) has been used particularly for modeling N, using airborne and satellite imagery mostly in temperate and tropical forests. However, there has been very little research conducted at these scales to model P, K, Ca, and Mg and few studies have focused on boreal forests. We report results of a study of macronutrient modeling using spaceborne IS and airborne light detection and ranging (LiDAR) data for a mixedwood boreal forest canopy in northern Ontario, Canada. Models incorporating Hyperion data explained approximately 90% of the variation in canopy concentrations of N, P, and Mg; whereas the inclusion of LiDAR data significantly improved the prediction of canopy concentration of Ca (R2 = 0.80). The combined used of IS and LiDAR data significantly improved the prediction accuracy of canopy Ca and K concentration but decreased the prediction accuracy of canopy P concentration. The results indicate that the variability of macronutrient concentration due to interspecific and functional type differences at the site provides the basis for the relationship observed between the remote sensing measurements (i.e., IS and LiDAR) and macronutrient concentration. Crown closure and canopy height are the structural metrics that establish the connection between macronutrient concentration and IS and LiDAR data, respectively. The spatial distribution of macronutrient concentration at the canopy scale mimics functional type distribution at the site. The ability to predict canopy N, P, K, Ca and Mg in this study using only IS, only LiDAR or their combination demonstrates the excellent potential for mapping these macronutrients at canopy scales across larger geographic areas into the next decade with the launch of new IS satellite missions and by using spaceborne LiDAR data.

Peatland vascular plant functional types affect methane dynamics by altering microbial community structure

Summary Peatlands are natural sources of atmospheric methane (CH4), an important greenhouse gas. It is established that peatland methane dynamics are controlled by both biotic and abiotic conditions, yet the interactive effect of these drivers is less studied and consequently poorly understood. Climate change affects the distribution of vascular plant functional types (PFTs) in peatlands. By removing specific PFTs, we assessed their effects on peat organic matter chemistry, microbial community composition and on potential methane production (PMP) and oxidation (PMO) in two microhabitats (lawns and hummocks). Whilst PFT removal only marginally altered the peat organic matter chemistry, we observed considerable changes in microbial community structure. This resulted in altered PMP and PMO. PMP was slightly lower when graminoids were removed, whilst PMO was highest in the absence of both vascular PFTs (graminoids and ericoids), but only in the hummocks. Path analyses demonstrate that different plant–soil interactions drive PMP and PMO in peatlands and that changes in biotic and abiotic factors can have auto‐amplifying effects on current CH4 dynamics. Synthesis. Changing environmental conditions will, both directly and indirectly, affect peatland processes, causing unforeseen changes in CH4 dynamics. The resilience of peatland CH4 dynamics to environmental change therefore depends on the interaction between plant community composition and microbial communities.

Impact of land cover characterization on regional climate modeling over West Africa

The impact of high resolution modern vegetation cover on the West African climate is examined using the International Centre for Theoretical Physics Regional Climate Model implementing the NCAR Community Land Model. Two high resolution 25 km long-term simulations driven by the output from a coarser 50-km resolution simulation are performed for the period 1998–2010. One high resolution simulation uses an earlier and coarser-resolution version of plant functional type distribution and leaf area index, while the other uses a more recent, higher-quality, and finer-resolution version of the data. The results indicate that the new land cover distribution substantially alters the distribution of temperature with warming in Central Nigeria, northern Gulf of Guinea and part of the Sahel due to the replacement of C4 grass with corn; and cooling along the coastlines of the Gulf of Guinea and in Central Africa due to the replacement of C4 grass with tropical broadleaf evergreen trees. Changes in latent heat flux appear to be largely responsible for these temperature changes with a net decrease (increase) in regions of warming (cooling). The improved land cover distribution also results in a wetter monsoon season. The presence of corn tends to favor larger precipitation amounts via more intense events, while the presence of tropical broadleaf evergreen trees tends to favor the occurrence of both more intense and more frequent events. The wetter conditions appear to be sustained via (1) an enhanced soil moisture feedback; and (2) elevated moisture transport due to increased low-level convergence in regions south of 10N where the most substantial land cover differences are present. Overall the changes induced by the improved vegetation cover improve, to some extent, the performance of the high resolution regional climate model in simulating the main West African summer monsoon features.

Understanding global change impacts on South African biomes using Dynamic Vegetation Models

The distribution of South African biomes is expected to be drastically altered as a result of climatic change and increasing atmospheric CO2 in the 21st century. Developing the capacity to anticipate change is of critical importance if we are to mitigate and efficiently adapt to the reorganization of South African vegetation cover. Dynamic Vegetation Models (DVMs) simulate the distribution and functioning of plant functional types (PFTs) and their interactions. Outputs include biome distribution maps, assessments of carbon cycling and the quantification of plant productivity, all of which can be produced for past, present and future conditions. DVMs were originally conceived of as analogs to general circulation models (GCMs) and applied globally, but to be unbiased globally necessitates choosing parameters and representing processes that may not be regionally appropriate. Models populated with a modified suite of PFTs and parameterized appropriately for local conditions are better suited to studies concerned with vegetation dynamics and global change impacts at the country or continent-scale. In their current form DGVMs do not include the plant types and key processes of many South African biomes. Therefore, while projections of global change impacts are available for biomes dominated by forest trees, savanna trees and grasses, little can be learned about some of our most biodiverse and threatened biomes, particularly the Fynbos and Thicket biomes, and the Succulent Karoo. We outline the limitations of existing DVMs and improvements required before reliable projections of global change impacts on South African biomes can be produced. Reparameterization of some PFTs and fire models could easily be achieved, and would lead to large improvements in model simulations. However, there remain numerous processes and facets of the ecology of South African vegetation that will limit the applicability of DVMs in their current form.

Fiber types of the anterior and lateral cervical muscles in elderly males.

The anterior and lateral cervical muscles (ALCM) are generally considered to be postural, yet few studies have investigated ALCM fiber types to help clarify the function of these muscles. This study aimed to systematically investigate ALCM fiber types in cadavers. Anterior and lateral cervical muscles (four scalenus anterior, medius, posterior muscles; five longus colli, five longus capitis taken bilaterally from one cadaver) were removed from four male embalmed cadavers (mean age 87.25 years). Paraffin-embedded specimens were sectioned then stained immunohistochemically to identify type I and II skeletal muscle fibers. Proportional fiber type numbers and cross-sectional area (CSA) occupied by fiber types were determined using stereology (random systematic sampling). Results were analyzed using ANOVA (P < 0.05) and descriptive statistics. Scalenus anterior had the greatest average number and CSA of type I fibers (71.9 and 83.7%, respectively); longus capitis had the lowest number (48.5%) and CSA (61.4%). All scalene muscles had significantly greater type I CSA than longus capitis and longus colli; scalenus anterior and medius had significantly greater type I numbers than longus capitis and longus colli. Some significant differences were observed between individual cadavers in longus colli for CSA, and longus capitis for number. The ALCM do not share a common functional fiber type distribution, although similar fiber type distributions are shared by longus colli and longus capitis, and by the scalene muscles. Contrary to conventional descriptions, longus colli and longus capitis have type I fiber proportions indicative of postural as well as phasic muscle function.

山西植物功能型划分及其空间格局

PDF HTML阅读 XML下载 导出引用 引用提醒 山西植物功能型划分及其空间格局 DOI: 10.5846/stxb201312042886 作者: 作者单位: 山西大学黄土高原研究所,山西大学生命科学学院 山西大学黄土高原研究所,山西大学生命科学学院;山西大学黄土高原研究所 作者简介: 通讯作者: 中图分类号: Q948 基金项目: 科技部科技基础性工作专项(2011FY110300); 山西省自然科学基金项目(2013011037-1); 山西省回国留学人员科研资助项目(20100012) Classification of plant functional types and spatial pattern in Shanxi Province Author: Affiliation: Institute of Loess Plateau,Shanxi University;Institute of Loess Plateau,Shanxi University,,School of Life Science,Shanxi University;Institute of Loess Plateau,Shanxi University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:随着全球气候变化的加剧,作为沟通陆地生态系统与气候变化的桥梁,植物功能型(Plant Functional Types, PFTs)越来越受到生态学家的关注。PFTs不仅是简化生态系统复杂性的有效工具,而且可将植物的生理生态过程、生物物理特征及物候变化等引入到动态植被模型中,研究气候变化下的植被反应及其反馈机制。为了在区域尺度上研究气候变化和植被反应,基于"生态-外貌"原则,依据植物特征(如生长型、叶的性状)及其对水分、温度的需求,结合区域的气候与地理条件,对山西植被进行植物功能型的划分,并在此基础上对其空间格局进行分析。结果表明:(1)山西植被可划分为19类植物功能型(其中包括4类栽培作物功能型),分别是:寒温性常绿针叶林、温性常绿针叶林、寒温性落叶针叶林、温性落叶阔叶林、高寒落叶灌丛、温性落叶灌丛、多年生禾草草原、多年生禾草草丛、多年生禾草草甸、多年生莎草草甸、多年生杂类草草原、多年生杂类草草丛、多年生杂类草草甸。1年生杂类草草甸、多年生豆科草原、果树、一年一熟栽培作物、一年二熟栽培作物和二年三熟栽培作物。植物功能型的划分和分布与山西植被区划有较好的一致性,基本反映了植物固有特征及其对水热条件的需求。(2)农作物在山西占有较大比重,占植被类型面积的53.15%,森林类型以温性常绿针叶林和温性落叶阔叶林为主,灌丛类型以温性落叶灌丛为主,草本类型中多年生禾草草丛占较大比例,占草本类型面积的50.98%。(3)由于水热条件及地理条件的差异,植物功能型(不考虑栽培作物)在各区域表现出较大差异,如多年生杂类草草原主要分布于北部地区,在南部并不存在这种植物功能型;森林类型的功能型主要分布于中、南部地区,且结构复杂、类型多样。(4)除栽培作物表现出较好的整体性和连通性,其他植物功能型均表现出不同程度的破碎化和离散化。(5)山西植物功能型整体上表现出较高的多样性,其中中部地区比其他地区的多样性和破碎化程度高,斑块类型更加趋向于离散的小斑块状,北部地区则以一年一熟栽培作物占明显优势,表现出较强的优势度,而南部地区并没有表现出很强的破碎度或优势度。 Abstract:Plant Functional Types (PFTs) have been paid increasing attention last decades as the linkage between terrestrial ecosystem and climate change with the intensification of global climate change. PFTs are not only an effective tool to simplify the complexity of ecosystem, but also helpful when exploring the response and feedback mechanism of plant to the climate changes by introducing plant physiological, ecological process, biophysical characteristics and phenological change into the vegetation dynamic model. In order to investigate climate change and response to vegetation at regional scale, PFTs classification system was proposed under the "eco-physiognomy" principle based on plant characteristics (such as vegetative form, leaf traits), thermal characteristics and water availability, combined with the regional climate and geographical conditions in Shanxi. Furthermore, the spatial pattern of PFTs was discussed in this paper. The results showed that: (1) Nineteen PFTs, including four PFTs of cultivated crops were identified, namely, cold warm-temperate evergreen coniferous forest, warm-temperate evergreen coniferous forest, cold warm-temperate deciduous coniferous forest, warm-temperate deciduous broadleaf forest, cold warm-temperate deciduous shrub, warm-temperate deciduous shrub, perennial grass steppe, perennial grass community, perennial grass meadow, perennial sedge meadow, perennial forbs steppe, perennial forbs community, perennial forbs meadow, annual forbs meadow, perennial Legume steppe, fruit tree, one crop per annual, two crop per annual, and three crop two annual. The classification and distribution of plant functional types reflect the inherent characteristics and demand for water and thermal of plants, being consistent with vegetation regionalization of Shanxi Province. (2) Crops are dominant in Shanxi, accounting for 53.15% of the total vegetation type area. Forest and shrubs types are dominated by warm-temperate evergreen coniferous forest, warm-temperate deciduous broadleaf forest and warm deciduous shrubs, respectively. Perennial grass community occupies a large proportion, accounting for 50.98% of the total area of the herbaceous types. (3) PFTs (except for crop cultivation) show bigger difference in different regions due to hydrothermal and geographical conditions. For example, perennial forbs steppe mainly distributed in north Shanxi, rather than in the south Shanxi. Compared with north Shanxi, the functional types of forest mainly distributed in the central and south Shanxi, and its structure and types were complex and diverse. (4) The cultivation crops show good integrity and connectivity, while the other PFTs show the fragmentation and discretization. (5) PFTs of Shanxi show integrally high diversity. Compared with the other two parts, more fragmentation and higher diversity are found in the central Shanxi. One crop per annual mainly distributed in North Shanxi, while south Shanxi did not exhibit significant fragmentation and dominance. 参考文献 相似文献 引证文献

Impacts of different plant functional types on ambient ozone predictions in the Seoul Metropolitan Areas (SMAs), Korea

Abstract. Plant functional type (PFT) distributions affect the results of biogenic emission modeling as well as O3 and particulate matter (PM) simulations using chemistry-transport models (CTMs). This paper analyzes the variations of both surface biogenic volatile organic compound (BVOC) emissions and O3 concentrations due to changes in the PFT distributions in the Seoul Metropolitan Areas, Korea. The Fifth-Generation NCAR/Pennsylvania State Meso-scale Model (MM5)/the Model of Emissions of Gases and Aerosols from Nature (MEGAN)/the Sparse Matrix Operator Kernel Emissions (SMOKE)/the Community Multiscale Air Quality (CMAQ) model simulations were implemented over the Seoul Metropolitan Areas in Korea to predict surface O3 concentrations for the period of 1 May to 31 June 2008. Starting from a performance check of CTM predictions, we consecutively assessed the effects of PFT area deviations on the MEGAN BVOC and CTM O3 predictions, and we further considered the basis of geospatial and statistical analyses. The three PFT data sets considered were (1) the Korean PFT, developed with Korea-specific vegetation database; (2) the CDP PFT, adopted from the community data portal (CDP) of US National Center for Atmospheric Research in the United States (NCAR); (3) MODIS PFT, reclassified from the NASA Terra and Aqua combined land cover products. Although the CMAQ performance check reveals that all of the three different PFT data sets are applicable choices for regulatory modeling practice, noticeable primary data (i.e., PFT and Leaf Area Index (LAI)) was observed to be missing in many geographic locations. Based on the assessed effect of such missing data on CMAQ O3 predictions, we found that this missing data can cause spatially increased bias in CMAQ O3. Thus, it must be resolved in the near future to obtain more accurate biogenic emission and chemistry transport modeling results. Comparisons of MEGAN biogenic emission results with the three different PFT data showed that broadleaf trees (BTs) are the most significant contributor, followed by needleleaf trees (NTs), shrub (SB), and herbaceous plants (HBs) to the total BVOCs. In addition, isoprene from BTs and terpene from NTs were recognized as significant primary and secondary BVOC species in terms of BVOC emissions distributions and O3-forming potentials in the study domain. A geographically weighted regression analysis with locally compensated ridge (LCR-GWR) with the different PFT data (δO3 vs. δPFTs) suggests that addition of BT, SB, and NT areas can contribute to O3 increase, whereas addition of an HB area contributes to O3 decrease in the domain. Assessment results of the simulated spatial and temporal changes of O3 distributions with the different PFT scenarios reveal that hourly and local impacts from the different PFT distributions on occasional inter-deviations of O3 are quite noticeable, reaching up to 13 ppb. The simulated maximum 1 h O3 inter-deviations between different PFT scenarios have an asymmetric diurnal distribution pattern (low in the early morning, rising during the day, peaking at 05:00 p.m., and decreasing during the night) in the study domain. Exponentially diverging hourly BVOC emissions and O3 concentrations with increasing ambient temperature suggest that the use of different PFT distribution data requires much caution when modeling (or forecasting) O3 air quality in complicated urban atmospheric conditions in terms of whether uncertainties in O3 prediction results are expected to be mild or severe.

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

Abstract. Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom–coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Analysis of complex phthalic acid based polyesters by the combination of size exclusion chromatography and matrix-assisted laser desorption/ionization mass spectrometry

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used in conjunction with size exclusion chromatography (SEC) to investigate a model polyester system based on phthalic anhydride–1,2-propylene glycol. The polyesters were synthesized with a 30% molar excess of glycol, with kinetic samples being removed during different intervals of the polyesterification reaction. SEC was used to track the course of the reaction by determining the molecular weight and molecular weight distributions before subsequent off-line coupling with MALDI-TOF MS as a selective detection method to determine the chemical composition, identify the functionality type distributions as well as assist in assigning structural conformations. Mass spectrometry analysis proved to be a highly effective tool to facilitate the identification of the narrowly dispersed fractions obtained from the chromatographic separations as well as serve as a core method to investigate the heterogeneous nature of the bulk kinetic samples. Through the hyphenation of these sophisticated polymer characterization techniques, information on the molecular heterogeneity of the model polyesters, showing a complex variety of possible distributions, was obtained.

Analysis of functionality-type distributions as a method for studying the kinetics of chemical reactions involving reactive oligomers

Critical chromatography is used to study the kinetics of reactions between polypropylene glycols and phenyl butyl isocyanate that simulate the production of polyester urethanes. The use of a two-detector version of chromatography makes it possible to monitor the concentration of the original, intermediate, and final oligomers and reveal the effect of one end group on the reactivity of the other separated by a long chain. The processing of the kinetic data makes it possible to determine the reaction-rate constants for macromolecules of different functionalities and to quantitatively describe the process behavior.

Deriving phytoplankton size classes from satellite data: Validation along a trophic gradient in the eastern Atlantic Ocean

In recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size.This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass (Brewin et al., 2010). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5mgm−3, rather than from 1.3mgm−3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78pg Chlacell−1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas.

Functionality-type distribution of poly(ethylene oxide) and poly(propylene oxide) macromonomers: Critical-chromatography study

Functionality-type distributions of macromomoners with poly(ethylene oxide) and poly(propylene oxide) chains are studied by chromatography under critical conditions. It is shown that, in the critical separation mode, separation of macromolecules with respect to size disappears and only information on the functionality-type distributions of the test samples may be derived. The critical conditions are determined experimentally with a normal phase (unmodified silica gel) for poly(propylene oxide) and with a reversed phase C18 for poly(ethylene oxide). The experimental retention volumes for bifunctional macromolecules are in satisfactory agreement with the values calculated under approximation of the Gaussian chain model.

Phylogenetic Distribution of Potential Cellulases in Bacteria

Many microorganisms contain cellulases that are important for plant cell wall degradation and overall soil ecosystem functioning. At present, we have extensive biochemical knowledge of cellulases but little is known about the phylogenetic distribution of these enzymes. To address this, we analyzed the distribution of 21,985 genes encoding proteins related to cellulose utilization in 5,123 sequenced bacterial genomes. First, we identified the distribution of glycoside hydrolases involved in cellulose utilization and synthesis at different taxonomic levels, from the phylum to the strain. Cellulose degradation/utilization capabilities appeared in nearly all major groups and resulted in strains displaying various enzyme gene combinations. Potential cellulose degraders, having both cellulases and β-glucosidases, constituted 24% of all genomes whereas potential opportunistic strains, having β-glucosidases only, accounted for 56%. Finally, 20% of the bacteria have no relevant enzymes and do not rely on cellulose utilization. The latter group was primarily connected to specific bacterial lifestyles like autotrophy and parasitism. Cellulose degraders, as well as opportunists, have multiple enzymes with similar functions. However, the potential degraders systematically harbor about twice more β-glucosidases than their potential opportunistic relatives. Although scattered, the distribution of functional types, in bacterial lineages, is not random but mostly follows a Brownian motion evolution model. Degraders form clusters of relatives at the species level, whereas opportunists are clustered at the genus level. This information can form a mechanistic basis for the linking of changes in microbial community composition to soil ecosystem processes.

Molar mass, chemical-composition, and functionality-type distributions of poly(2-oxazoline)s revealed by a variety of separation techniques

Detailed characterization of synthetic polymers often required multiple advanced separation technologies since the various molecular distributions present, e.g. polymer molar mass, chemical composition, functionality distributions, etc. are generally mutually dependent. The complexity of polymeric materials necessitates the use of a variety of analytical methods, either in conjunction or in integrated (“hyphenated”) systems. Poly(2-oxazoline) homo- and copolymers with two different side groups rendering the systems hydrophobic, i.e. phenyl and dec-9-enyl substituents, synthesized by living cationic ring-opening polymerization, were investigated. The average chemical composition obtained by pyrolysis-gas chromatography–mass spectrometry (Py-GC–MS) corresponded well with the theoretical composition. The chemical-composition distribution was studied with gradient elution liquid chromatography (GELC) using water and tetrahydrofuran as mobile-phase components. Statistical copolymer samples – in contrast to their block copolymer analogues – revealed two well-separated peaks in GELC. By combining GELC with size-exclusion chromatography (SEC) it was confirmed that the GELC separation was not based on differences in the molar mass. A more likely explanation of the GELC results is the presence of an ionic fraction in the samples of statistical copolymers resulting from either chain-transfer reactions or termination by addition of water. This hypothesis was confirmed with capillary electrophoresis.

Wetland chronosequence as a model of peatland development: Vegetation succession, peat and carbon accumulation

Model validation experiments are fundamental to ensure that the peat growth models correspond with the diversity in nature. We evaluated the Holocene Peatland Model (HPM) simulation against the field observations from a chronosequence of peatlands and peat core data. The ongoing primary peatland formation on the isostatically rising coast of Finland offered us an exceptional opportunity to study the peatland succession along a spatial continuum and to compare it with the past succession revealed by vertical peat sequences. The current vegetation assemblages, from the seashore to a 3000 year old bog, formed a continuum from minerotrophic to ombrotrophic plant communities. A similar sequence of plant communities was found in the palaeovegetation. The distribution of plant functional types was related to peat thickness and water-table depth (WTD) supporting the assumptions in HPM, though there were some differences between the field data and HPM. Palaeobotanical evidence from the oldest site showed a rapid fen–bog transition, indicated by a coincidental decrease in minerotrophic plant functional types and an increase in ombrotrophic plant functional types. The long-term mean rate of carbon (C) accumulation varied from 2 to 34 g C/m2 per yr, being highest in the intermediate age cohorts. Mean nitrogen (N) accumulation varied from 0.1 to 3.9 g N/m2 per yr being highest in the youngest sites. WTD was the deepest in the oldest sites and its variation there was temporally the least but spatially the highest. Evaluation of the HPM simulations against the field observations indicated that HPM reasonably well simulates peatland development, except for very young peatlands.

ASSESSMENT OF PLANT FUNCTIONAL TYPES IN TROPICAL ARID AND SEMI-ARID ECOSYSTEMS OF INDIA USING REMOTE SENSING DATA AND GIS

Abstract. Tropical ecosystems undergo changes caused by season, climate or multiple anthropogenic impacts. Such changes may cause gradual or rapid shifts from one state to another. There has been a focus on functional classifications of plants to find tools for monitoring and assessing species status in changing environments. It has been recognised that plant biological characteristics can be related to their response to predominant environmental factors and interactions between other organisms. These findings have resulted in a search for plant functional types (PFTs) that are user-defined groups of species with similar response to environmental resources and disturbance associated to common biological traits. Now, identification of plant functional types is priority area in the climate change research. Satellite Earth observation data is an important tool in providing considerable information on extracting PFT information at global and regional levels. From the modelling perspective, some of the current needs are the refinement of processes that govern community assembly, such as natural and anthropogenic disturbances. PFTs used in large-scale models are insufficient to represent the diversity of responses in natural plant communities. The currently available MODIS PFT map was generated by re-labeling the IGBP land cover type classes. However, the error magnitudes of the MODIS PFT product and their spatial and temporal distributions have not been fully characterized. Remotely sensed derived information of the phenology, community composition and vegetation structure are the key inputs to integrate with the variability in precipitation and temperature to map the spatial distribution of Plant functional types. PFTs allows accurate representation of the land surface by separately specifying the composition and structure of PFTs within a grid cell. Very little research efforts are discernible in India that explicitly address the PFTs. In the present study five natural vegetation systems were studied along arid, semi-arid and sub-humid regions of Indian Desert and Aravallis of Rajasthan, India, with a distance of 600 km. The annual precipitation decreases from as high as 1600 mm in the south to 700 mm in the north-east and 100 mm in the west. The study is based on the integrated approach of remote sensing, GIS, and phytosociology. In the step 1, vegetation type map was prepared using multi-season IRS P6 LISS III data. Screening of plant traits was done based on field observations and literature. Phytosociological data pertains to 500 sample plots was used to identify plant functional traits of 900 species at morphological level. The vegetation classification scheme at regional level identified thorn forest, dry deciduous forest, broad leaved forest, woodland, shrubland and grasslands. Five plant traits selected in the study were significant for tropical environments. Attributes such as leaf size, leaf texture, spinescence, stem diameter and bark consistency were categorized systematically. Ordination analysis was carried out across the environmental gradient. Plant functional traits were measured on 20 individuals per species at each site. Environmental information was integrated to identify plant trait response. The spatial trends in PFTs were analysed and compared across the vegetation types, along the gradient of land surface temperature, climate, elevation and time integrated NDVI. Results established the occurrence of recurrent patterns of association among selected plant traits. Functional response groups were identified by summarizing results and relating them to individual species. Finally phytoclimatic map was prepared to represent spatial distribution of PFTs. The species with of functional traits of representing microphylls, sclerophyll, rough bark, spinescence and therophyte are demarcated as drought tolerant traits. Drought Intolerant PFTs are represented by macrophyll, malacophyll, smooth Bark, non spinescent stems and leaves. Biological spectrum of Desert national park, Jaisalmer and and Ajmer represents therophytic climate (below 600mm rainfall) while Sariska and Mt. Abu are of therophanerophytic (&gt;600mm rainfall). The higher proportion of microphylls and therophytes are distributed within tropical arid environments. The dominance of the drought tolerant PFTs increased towards west while the dominance of the drought intolerant PFTs increased in southern and northern parts of Rajasthan. Detecting the change of spatial characteristics of plant species under precipitation gradients would be helpful to study species dynamics in a large region under environmental gradient. On the basis of easily-measured plant traits and phytosociological surveys, the present approach summarized the complexity of tropical vegetation into a relatively few PFTs. The present study open up new possibilities for understanding plant trait and environment relationship and developing PFT classification in tropical regions.

Tree mortality in dynamic vegetation models – A key feature for accurately simulating forest properties

Dynamic vegetation models are important tools in ecological research, but not all processes of vegetation dynamics are captured adequately. Tree mortality is often modeled as a function of growth efficiency and maximum age. However, empirical studies have shown for different species that slow-growing trees may become older than fast-growing trees, implying a correlation of mortality with growth rate and size rather than age. We used the ecosystem model LPJ-GUESS to compare the standard age-dependent mortality with two size-dependent mortality approaches. We found that all mortality approaches, when calibrated, yield a realistic pattern of growing stock and Plant Functional Type (PFT) distribution at five study sites in Switzerland. However, only the size-dependent approaches match a third pattern, i.e. the observed negative relationship between growth rate and longevity. As a consequence, trees are simulated to get older at higher than at lower altitudes/latitudes. In contrast, maximum tree ages do not change along these climatic gradients when the standard age-dependent mortality is used. As tree age and size determine forest structure, our more realistic mortality assumptions improved forest biomass estimation, but indicate a potential decline of carbon storage under climate change. We conclude that tree mortality should be modeled as a function of size rather than age.

Evaluation of the New CNDV Option of the Community Land Model: Effects of Dynamic Vegetation and Interactive Nitrogen on CLM4 Means and Variability

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon–nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen (N) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen–carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger “regulator” of variability compared to the other configurations. Discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate–vegetation interactions.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.