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Date Created: 11/02/15
5 His TRENDS in Ecology and Evolution Vol22 No5 Full text provided by wwwsdencedirectoom ScienceDirect The relevance of phylogeny to studies of global change Erika J Edwards1 Christopher J Still1 and Michael J Donoghue2 1 Geography Department and the Institute for Computational Earth System Science University of California Santa Barbara CA 93106 USA 2Department of Ecology and Evolutionary Biology and the Peabody Museum of Natural History Yale University New Haven CT 06511 USA Phylogenetic thinking has infiltrated many areas of biological research but has had little impact on studies of global ecology or climate change Here we illustrate how phylogenetic information can be relevant to under standing vegetation atmosphere dynamics at ecosys tem or global scales by reanalyzing a data set of carbonic anhydrase CA activity in leaves that was used to estimate terrestrial gross primary productivity The original calculations relied on what appeared to be low CA activity exclusively in C4 grasses but our analyses indicate that such activity might instead characterize the PACCAD grass lineage which includes many wide spread C3 species We outline how phylogenetics can guide better taxon sampling of key physiological traits and discuss how the emerging field of phyloinformatics presents a promising new framework for scaling from organism physiology to global processes Introduction The integration of phylogenetics with other areas of biology has grown more prevalent in recent years The rst and most obvious connections were made in evolutionary biology eg character evolution and adaptation molecular evolution developmental biology and historical biogeogra phy but important links have also been made in elds as farreaching as community ecology 1 and medicine 2 By contrast phylogenetic thinking and analytical methods appear to have had little impact in ecosystem ecology or global change research Is this because there are no mean ingful connections between these areas or is it that this particular intersection has yet to be explored We argue here that a productive area of overlap between these elds does exist Understanding biogeochemical cycles for example depends upon understanding how compounds are processed by the biosphere which ulti mately is influenced by the physiology of individual organ isms We know that physiological traits vary among different groups of organisms and that these differences originated as evolutionary innovations along the branches of the tree of life It stands to reason therefore that knowing how organisms are related to one another will help us to better understand how key physiological traits are distributed across species and in turn across biomes Corresponding author Edwards EJ eedwardsicessucsbedu Available online 12 February 2007 The existence of signi cant physiological differences among organisms has been recognized by those modeling global processes This is most evident in the widespread recognition of functional types most commonly plant func tional types or PFTs 34 particularly among dynamic global vegetation models 5 7 Different authors use differ ent categories of PFTs but in general these are meant to capture observed differences in functional traits that influ ence ecosystemlevel processes Two particularly wellused PFTs are CS versus C4 plants C4 plants utilize an evolu tionarily derived photosynthetic pathway that concentrates C02 at the site of carbon assimilation inside the leaf This results in C4 plants having typically higher maximum photosynthetic rates and higher water and nitrogen use ef ciencies compared with C3 plants key traits that can affect global carbon water and nutrient cycles The use of PFTs is an improvement over assuming that all plants are functionally equivalent However the species assigned to any particular PFT will usually represent multiple evolutionary origins of that PFT standard growth form categories trees shrubs herbs and succulents and even photosynthetic pathways C4 and crassulacean acid metabolism have evolved independently many times and in distantly related plant lineages Each separate origin of a particular PFT occurred within a different organismal context and will be associated with distinct anatomical and biochemical traits that could result in different functional performance eg grass species representing separate ori gins of C4 photosynthesis respond differently to elevated C02 8 In addition species that have been assigned to different PFTs eg trees versus herbs might perform sim ilarly if they both happen to be members of a lineage that evolved a key physiological trait That is relevant physi ology can be conserved through evolutionary transitions in growth form For these reasons a phylogenetically based classi cation scheme might be a good alternative to traditional PFTs for organizing physiological diversity into functional units for modeling purposes We illustrate this point by reanalyzing data from a study that used the differential isotopic discrimination of atmos pheric C02 by PFTs during photosynthesis to estimate terrestrial gross primary productivity GPP We conclude that phylogenetics is highly relevant to globalscale pro blems However establishing practical collaborations bet ween phylogeneticists and global ecologists depends upon the further development of phyloinformatics especially the www3ciencedirectcom 01695347 see front matter 2007 Elsevier Ltd All rights reserved doi101016jtree200702002 244 TRENDS in Ecology and Evolution Vol22 No5 ability to mine data on the geographical distributions of species within a phylogenetic framework Photosynthetic discrimination of 6160130 and the global carbon cyc e Current estimates suggest that approximately half of the increased atmospheric C02 resulting from fossil fuel com bustion and deforestation is reabsorbed into terrestrial and oceanic systems 9 13 It is still unclear however how this carbon sink is distributed among and within marine and terrestrial ecosystems despite this knowledge being crucial for projecting future atmospheric C02 levels Understanding the mechanisms underlying terres trial carbon uxes and their temporal variation is thus a major goal of carbon cycle science Stable isotope chemistry has proven useful in helping to resolve processes within the global carbon cycle 11 For instance it is now clear that the terrestrial biosphere is primarily responsible for setting the 3930 0 ratio of atmos h ric C02 referred to as 81803 15 17 Furthermore photosynthesis and respiration the two main biological processes involved in land atmosphere carbon exchange each produce a unique isotopic imprint on 81803 This results mainly from an effective discrimination against eavier C160 13930 molecule by terrestrial photosynthesis Box 1 Because of this analysis of 81803 potentially enables estimation of terrestrial ecosystem GPP and thus changes in GPP in response to climate variation There is additional potential for 81803 to resolve differences in GPP among different types of terrestrial ecosystem eg grass lands versus forests 18 which could become an important tool in monitoring ecosystem responses to climate change hotosynthetic discrimination against 0160180 A18 is caused by several processes rst water in plant leaves is typically enriched in the heavier molecule H2180 because the lighter H2 60 evaporates more easily into the atmos phere Second there is an exchange of oxygen atoms between leaf water and dissolved C02 in the leaf meso phyll such that many of the heavy 13930 atoms are trans ferred to C02 molecules The degree of oxygen isotopic equilibration between leaf 002 and H20 termed Eq depends upon the activity of the enzyme carbonic anhy rase CA Lastly much of the atmospheric C02 that diffuses into the leaf and becomes dissolved then diffuses back into the atmosphere before it can be incorporated into the next step of photosynthesis Owing to the isotopic Box 1 How does 0150180 discrimination by photosynthesis work When the stomata of a plant are open atmospheric C02 passively diffuses into the leaf along a concentration gradient where it is then dissolved in mesophyll cell water CA is found in the leaves of all plants and catalyzes the hydration reaction Equation ll C02 H20 lt gt H2C03 4 H HCO 3 Eqn I This results in the formation of bicarbonate ions HCO al which react with PEP carboxylase in the first step of the C4 photosynthetic pathway 31 The importance of C02 hydration in C3 plants is less clear but it is presumed to aid in C02 diffusion into the chloroplast and in the maintenance of a steady supply of C02 for the Calvin cycle 3233 the metabolic pathway that fixes carbon in all photosynthetic organisms The hydration of C02 in the mesophyll results in an isotopic fingerprint of photosynthesis on atmospheric C02 because of two factors First leaf water is generally enriched in H2130 relative to source soill water owing to the differential evaporation of the lighter H2130 molecules through the stomata During the C02 hydration reaction oxygen atoms from C02 and H20 are often switched resulting in 130 labeled C02 molecules Equation Ill C1502H2150 lt gt H C1501502 lt gt C150150 H2150 Eqn Second it is estimated that up to 60 of the gross C02 flux into leaves each year returns to the atmosphere without being fixed by photosynthesis 1534 Because many of these molecules have been labeled with 130 owing to CA activity this retroflux causes an 30 enrichment of the C02 outside of the lea how much of the 130 from leaf water is transferred to C02 Previous work on estimating global values of C160130 discrimination by photosynthesis has assumed that the oxygen isotopic equilibrium between C02 and H20 eeql results from a temperature dependent fractionation factor 35 and is not limited by CA activity 15 17 Gillon and Yakir 19 investigated this assumption by calculating the sensitivity of GM to potential variation in CA activity of an individual plant Equation llll em 1 e W3 Eqn lll where the k39r is the product of a CA rate constant kl and C02 in leaf residence time T 36 The authors translated this term into two measurable components in viva CA activity which is an estimated variable based on CA leaf assays gas exchange measurements and wwwsciencedirectcom leaf temperaturel and gross flux of C02 from the atmosphere to the leaf Their survey of 52 plant species demonstrated extreme variation in egg from 003 in Digitaria sanguinalis a C4 grassl to 100 in a variety of species representing woody and herbaceous eudicots monocots and conifers Figure ll 19 They arguethat low equilibrium values result in a significantly reduced isotopic imprint of photo synthesis on atmospheric C02 and that this has major implications for estimating global GPP see main textl 107 i g u O6 v n G I 047 I 02 I l l 00 4 l l l l t9 09 gt9 gt9 0 9 599 599 6 v v0 v9 00 as 99 0 we 0 0 Own 639 Om 6 a9 9 TRENDS in Ecology amp Evolution Figure I Mean values of eq using supplemental data from 18 sorted into the FT categories used by Gillon and Yakir 18 in this case the C3 Monocot39 FFT refers to all C3 rnonocots otherthan grasses the C4 Grass39 FFT also includes a C4 sedge Cyperus and the Herb39 FFT refers to herbaceous eudicots Bold lines inside the box are median values 85 confidence intervals are represented by the dashed lines w exchange with leaf water many of these molecules are now labeled with 180 Estimates of global A18 have been made with the assumption that CA activity is universally high in all plants and so isotopic equilibration between C02 an H20 851 is complete 851 1 111516 Box 1 However work by Gillon and Yakir 19 2 1 challenges this assump tion In particular the authors demonstrate an extreme variation in effective CA activity and Eq among 52 plant species that would lead to large differences in A18 19 They argue that as a group C4 grasses show the greatest reductions in A18 Box 1 Figure I and that previous estimates of C4 A18 have led to a signi cant underestima tion of C4 GPP This has major implications for global GPP as C4 plants are currently estimated to account for 18 25 of global photosynthesis 2223 and their prevalence is increasing in tropical areas where they often replace low land forests following deforestation Gillon and Yakir 19 suggest that the miscalculation of global A18 is currently underestimating global GPP by as much as m20 t is clear that the C4 grasses sampled by Gillon and Yakir 19 when averaged as a unit have a signi cantly different mean value in CA activity and in resulting 83 Box 2 Assessing trait correlations using phylogenetic methods TRENDS in Ecology and Evolution Vol22 No5 245 compared with the other PFT categories Box 1 Figure 1 However when the data are viewed in a phylogenetic context the situation is not so straightforward Fortu nately the complexities that emerge open up several new and productive avenues of research Insights from phylogeny To explore the data set of Gillon and Yakir 19 in a phylogenetic context we constructed a composite phylo geny of their 52 sampled species from previously published studies gure 1 Box 2 Using this tree in a simple trait mapping exercise can provide important clues about the relationships between 851 PFTs and major plant lineages Focusing rst on gure 1a it appears that there have been several reductions in 831 but the lowest values correspond with a major lineage of grasses known as the clade consisting of the panicoid arundinoid chloridoid centothecoid aristidoid and danthonioid grass lineages 4 om this perspective Echinochloa in view of its nested position within the PACCAD clade has an unex pectedly high value of 088 Onto the tree in Figure 1b we have mapped the functional types referred to by Gillon and Yakir 19 Figure 1 main text depicts the phylogenetic relationships of the 52 species used in the Gillon and Yakir 19 study with the exception of an unidentified C4 grass which we excluded from our analyses Relationships among the major plant lineages were assigned using the classification of the Angiosperm Phylogeny Group 37 and resolution within major clades was determined according to individual studies 24263839 and the Angiosperm Phylogeny Website httpwwwmobotorgMOBOTresearchAPwebl All branch lengths were arbitrarily assigned to 10 This approach to tree building does not provide meaningful branch length informa tion for example in our composite tree Cyperus sp 1 and Cyperus sp 2 are sister species as are Dais continifolia and Hibiscus sp and hese species are separated by similar branch lengths However it is likely that Dais and Hibiscus diverged from one another much earlierthan did thetwo Cyperusspecies In an attempt to account for this we constructed a second tree with identical topology butwith branch lengths scaled to time using independently calculated node age estimates of major clades 40 This second tree is also imperfect but better represents the relative phylogenetic distance between taxa To test for significant phylogenetic signal of physiological traits we used the ACT software module in Phylocom v 322 41 For a given trait we generated a null distribution of mean divergence values of sister lineages by randomly redistributing tip values of traits across the tree 1000 replications We then compared divergence values of the real data with our distribution a trait was considered significantly labile if real data trait divergences were greater than the greatest 50 of 1000 replicates p lt 005 and significantly conserved if real data trait divergences were smaller than the smallest 50 of 1000 replicates p lt 005 We ran these analyses using both sets of branch lengths and with normal and In transformed trait data xon sampling did not enable us to test directly forthe correlated evolution of C4 grass and low 9 as there are only two transitions between C3 and C4 photosynthesis captured in the grasses although the C4 grasses included probably do represent multiple origins of C4 photosynthesis However there are four potential transitions from C3 to C4 photosynthesis across the entire tree and in some parts of their discussion Gillon and Yakir 19 associated low CA activity with C4 photosynthesis in general rather than with C4 grasses in particular We therefore tested directly for correlations between photosynthetic pathway and shifts in 3eq as well as the other physiological traits www3ciertcedirectcom measured Significance of independent contrasts were assessed by calculating 95 confidence intervals around the mean contrast value using a one sample t distribution 42 traits were considered either positively or negatively correlated with the evolution of C4 photo synthesis if the value zero fell outside the 95 confidence interval p lt 005 Figure ll Mean contrast value TRENDS in Ecology amp Evolution Figure I Means and confidence intervals for independent contrast analyses of three physiological traits and C4 photosynthesis using supplemental data from tails A mean contrast value of zero indicates that the two traits are not significantly correlated As Zero falls within the 85 confidence interval for G we cannot reject the null hypothesis of zero correlation between 89 and C photosynthesis Two other traits photosynthetic rate A and internal leaf COZ concentration C show significant correlation with C4photosynthesis as would be expected based on what we know about c4 plant physiology Physiological data were lnrtransforrned before analysis 246 TRENDS in Ecnlngy and Evnlutinn Vol22 No5 Conifers a Juniperus sxcelsa b Metasequoia glyptostroboidesi Sequoia sempervirens Podosarpus alcatus Araucari39a excelsia Ow Plant CI 001 0109 functional type 1 0109 0 208 CI 0208 0 307 Cl 0 CI 0307 7 0 406 I Treeshrub CI 0406 7 0505 I C I 0505 0604 I C4 herb 0604 0703 I CS monocot I 0703 0802 C3 grass I 0802 7 0901 Angiosperms C4 monocot I 0901 7 10 1 0 Monocots Arum gap Crocpsmla 5p Ruscus p Asparagus sp Comm lina oommunis tha Sp Cyperus sp Cyperus sp 1 is e or r w 1 rm chuigrurr Eudicots Platanus orientalis TRENDS in Ecology E EvaLilian Figure 1 incorpora ng a phyiogene c perspecfive 39imo smd39ies of giobai ecoiogy This phyiogene cvee represems We evoimionary reia onsh39ips of species sarnpied by Giiion and Yakir 18 who used rnean vaiues of G a cornpiex phoiosynihesisreiaiedxraii mm ieaves a Vaceabie isoiopic imprim on airnospheric COZ binned by piam funcfionaHype PFTMo esfimaie GPP Mapping speciesvaiues omq a and PFT o 39 H p a xhe39irevoiud nary ni iy Sorne FFT caiegor39ies correspond w39iih paniouiar phyiogene c iineages eg conifers whereas oihers have evoived rnuhipie fimes eg c3 herbs 0q exhibhed signi cam phyiogene csignai when mapped omome phyiogeny Box 2 owing prirnariiyio We iowesi 0q vaiues being concemraied in We FACCAD oiade ofgrasses This suggesis HM 39 39 39 39 4 L quotFT raiidmm iow L 39 i mi ha 4 The39incius39ion r n u 9 of 3H PACCAD grasses 39in We originai anaiyses wouid have iead 0 a higher es mafion of GPP www50iencedirectcom w How well do these PFTs correlate with the Eq values in Figure 1a On the surface there does not appear to be a strong correlation between the evolution of C4 photosyn thesis and low Eq values Thus we do not see reduced values in C4 eudicot herbs iie Amaranthus or in C4 monocots outside of the grasses iie Cyperus sp 2 The best correlation is within the grasses where the C4 grasses generally show low values with the exception of Echino chloa already noted However in this context the C3 grass Phragmites with its low 83 value appears out of place We return to these apparent exceptions later but it is rst important to test more rigorously these initial percep tions derived by inspection of Figure 1 Using the methods described in Box 2 we can ask whether any of the phys iological traits measured by Gillon and Yakir 19 exhibit signi cant phylogenetic signal suggesting that they are evolutionarily conserved traits and whether low Eq or any of the other physiological traits are correlated with C4 photosynthesis in general or with the C4 grass PFT in particular All the physiological traits measured by Gillon and Yakir 19 demonstrate a signi cant phylogenetic signal p lt 001 when tested using either set of branch lengths and analyzing normal or lntransformed data Box 2 This is due mainly to values in the PACCAD grass clade being distinctly different from all other taxa In our tests for correlated evolution between C4 photosynthesis and the measured physiological traits we could not reject the hypothesis of a mean shift of zero in 85 indicating that the evolution of C4 photosynthesis is not signi cantly correlated with a change in 851 It should be stressed however that the small number of transitions between photosynthetic pathways in the dataset n 4 afforded limited statistical power Despite this there was a signi cant correlation between C4 photosynthesis and two other traits commonly associated with the C4 pathway photo synthetic rate A was positively correlated with C4 photo synthesis and internal leaf C02 concentration Ci was negatively correlated Box 2 Figure 1 Unfortunately it was not possible to evaluate the statistical signi cance of a possible correlation between low Eq an grasses in particular because the sampling of species in the original data set only captured at most two transitions between photosynthetic pathway within the grasses Echinochloa Phragmites and eeq We have highlighted what we feel is the most important pattern to emerge from these analyses the lowest values of Eq are found primarily in the PACCAD clade of grasses Because all the sampled C4 grasses are also from the PACCAD clade it might still seem reasonable to associate low Eq values with the C4 grass PFT Focusing in on this clade however the two exceptions mentioned earlier lead us to think otherwise First although Phragmites australis is a C3 species it exhibits similarly low values to other PACCAD clade members Without the knowledge that Phragmites is a member of the PACCAD clade as opposed to another major grass lineage the BEP clade 24 which consists of exclusively C3 species and to which all other sampled C3 grasses belong one might dismiss the low Phragmites value as anomalous just as Gillon and Yakir www5ciencedirectcom TRENDS in Ecology and Evolution Vol22 No5 247 19 ignored the higher 85 values in Amaranthus When regarded within a phylogenetic context however the Phragmites Eq is consistent with its nearest relatives the PACCAD grasses as are the Amaranthus species with their relatives other eudicots The value that instead is that ofquot 7 Prusgalli a C4 PACCAD member with a high Eq of 088 Why might Echinochloa have such a different value from the other sampled PACCAD species Although it is not evident from gure 1 Echinochloa probably represents an independent origin of C4 photo synthesis from the other C4 grasses included in the study It is the only C4 member of a C3 lineage of forest unders tory grasses referred to as the forestshade clade 2526 Although we do not currently have data on the 83 values of other members of this clade the high Eq value of the sampled Echinochloa makes it clear that the transition to C4 photosynthesis was not associated with a dramatic reduction in 85 providing a second argument that low 85 and the C4 grass PFT are not necessarily linked To investigate the matter further one could use phylogenetic information to guide a more strategic sampling of grasses to survey for CA activity and resulting 85 values It is estimated that there have been 11 inde pendent origins of C4 photosynthesis in the grasses 27 at least seven of which occurred in the Panicoideae alone 2527 To test whether being a grass and performing C4 photosynthesis is correlated with low 83 one could measure 85 in representative taxa from each of the 11 C4 lineages and their respective C3 relatives If one found a signi cant correlation between the evolution of C4 photo synthesis and a reduction in 85 then that would provide strong support for modeling the C4 grass PFT with low Eq values If one instead found that shifts in photosynthetic pathway are not associated with shifts in 851 and that low 85 is highly conserved and largely representative of the PACCAD grasses how would that understanding inform global biogeochemical modeling efforts One might argue that it makes no difference as all C4 grasses are found in the PACCAD clade and would thus all have low 85 values anyway As discussed earlier however there are also many C3 grasses in this clade that would also have low 85 values and these include some of the most ecolo gically dominant grasses eig Phragmites the common reed Arundo the European reed grass and Cortaderia the pampas grass of South America Phragmites australis for example is now common in many temperate areas of the world and in North America it is rapidly expanding its range and forming dense monospeci c stands over large areas 2829 Figure 2 Taken together we believe that the C3 PACCAD ecological dominants could signi cantly in uence global A18 which suggests that assigning them an erroneously high value of Eq would lead to large miscalculations in carbon cycling on a global scale Qfanrlc nnf an Global change research and phyloinformatics So how do we incorporate phylogenetic information into studies of global ecology and climate change This knowl edge could be immediately utilized by those modeling C160180 ecosystem atmosphere exchanges at a particular 24B TRENDS in Ecnlngy and Evnlutinn Vol22 No5 a b Figmzri i4 wail a C3 grass of he PACCAD oiade Phragmi39tes austrai39s is a good examoie of some of the dominani c3 grasses that our onyiogeneiio anaiyses indioaie might snare iow 6q vaiues wiin ineir c4 reiaiives Such c3 grasses represeni nigniy oroduoiive and uoiguiious species and assigning them erroneous 6q vaiues oouid signi oaniiy a eoi esiimaiions of giooai GPP a in many regions P austrai39s is an aggressive giooai iemoeraiureoreoioiiaiion daiasei WoridCiim mo and eooiogioai nione modeiing MAXVENT 43 Ar nignesi orooaoiiiiy of P austrai39s ooourrenoe wnereas those in dark oiue represeni zero probability Wiin funher deveioomeni of onyioinformaiios we envision oeing aoie to modei geograonioai disiriouiions of eniire oiades as easiiy as a singie soeoies site that is known to have PACCAD clade CS grasses It is currently more dif cult to translate this knowledge to regionalscale and globalscale analyses Our argument is that the area that is assigned a lower 85 value for purposes of global calculations should be increased to include the distributions of Phragmites and other ecologi cally dominant CS PACCAD asses There are many global vegetation models that currently estimate the location and extent of C4 grassdominated ecosystems 2330 but not PACCADclade dominated ecosystems One possibility would be to estimate the distribution of individual species through analyses of satellite imagery or other remotesensing techniques This might be possible in certain cases eg Phragmites where large monospecifc stands could be detected but we doubt that the geographi cal ranges of many species could be determined in this way A different and we believe quite promising approach will be enabled by the further development of phyloinfor matics Digitization efforts now being undertaken by natural history institutions worldwide are yielding open online access to the geographical data associated with museum specimens eg the Global Biodiversity Infor mation Facility httpwwwgbiforg At the same time the development of georeferencing tools and GISbased www5ciencedirectcom modeling methods make it possible to generate predictive range maps for species from data on specimen labels gure 2 If these capabilities could be linked with rapidly expanding knowledge on phylogenetic relationships eg TreeBASE httpwwwtreebaseorg it would be possible to automate the assembly of geographical range infor mation for entire clades Thus for example we could infer the geographical range of the PACCAD grasses by con necting information on clade membership to specimen databases and submitting these data to a linked cascade of georeferencing nichemodeling and mapping webser vices These results could then be used in more nuanced models designedto estimate global ecosystem parameters such as GPP Accuracy could be improved still further with the inclusion of relative abundance information gath ered from online databases of vegetation plot surveys eg httpwwwsalviasnet httpwwwvegbankorg which might also be available in some cases Conclusion In summary we see both the need and the real possibility to develop a productive link between phylogenetics and global biology Phylogenetic knowledge is expanding rapidly and it can now be used to orient and to improve studies including those of global change that concern the evolved functional traits of organisms As we have shown variation in the relevant physiological attributes does not always correspond neatly with the traditional plant func tional categories used in ecosystemlevel studies We are con dent that the accuracy of modeling efforts can be improved by taking the phylogenetic distribution of these key traits into account and we orward to the design of the phyloinformatics tools that are necessary for practical applications on a global scale Acknowledgements We thank T Kellogg C Webb and two anonymous reviewers for their thoughtful comments and discussions of these issues References 1 Webb CO et al 2002 Phylogenies and community ecology Annu Rev Ecol Syst 33 475 505 2 Rambaut A et al 2004 The causes and consequences of HIV evolution Nat Rev Genet 5 52 61 3 Diaz S and Cabido M 2001 Vive la difference plant functional diversity matters to ecosystem processes Trends Ecol Evol 16 46 655 4 Chapin FS et al 1996 Plant functional types as predictors of transient responses of arctic vegetation to global change J Veg Sc 7 347 358 5 Bonan GB et al 2003 A dynamic global vegetation model for use with climate models concepts and description of simulated vegetation dynamics Glob hange Biol 9 1543 1566 6 Defr39ies RS et al 1995 Mapping the landsurface for global atmospherebiosphere models toward continuous distributions of vegetations functionalproperties J Geophys Res Atmos 100 20867 20882 7 Sitch S et al 2003 Evaluation of ecosystem dynamics plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model Glob Change Biol 9 161 185 8 Kellogg EA et al 1999 Growth responses of C4 grasses of contrasting origin to elevated C02 Ann Bot 84 279 288 9 Broecker WS et al 1979 Fate of fossilfuel carbon dioxide and the global carbon budget Science 206 409 418 10 Francey RJ et al 1995 Changes in oceanic and terrestrial carbon uptake since 1982 Nature 373 326 330
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