Close Home
iForest - Biogeosciences and Forestry
vol. 4, pp. 172-175
Copyright © 2011 by the Italian Society of Silviculture and Forest Ecology
doi: 10.3832/ifor0590-004

Collection: COST Action FP0903 (2010) - Rome (Italy)
“Research, monitoring and modelling in the study of climate change and air pollution impacts on forest ecosystems”
Guest Editors: E Paoletti, J-P Tuovinen, N Clarke, G Matteucci, R Matyssek, G Wieser, R Fischer, P Cudlin, N Potocic

Review Papers

Effects of increasing CO2 on trees and intensively monitored plots: research needs in view of future ecosystem studies

P. MichopoulosCorresponding author


There is a growing increase in the impact of elevated atmospheric CO2 on forest trees and forest ecosystems. This is not surprising as forests cover some 27% of the total land surface but account for some 70% of terrestrial net primary production ([27]). Moreover, more than 85% of the total plant C on earth and between 60-70% of the total soil C is contained in forests ([10]). The atmospheric concentration of CO2 is currently increasing at the rate of 3.3 billion tons of C per year ([17]). Very good reviews have been published about the consequences of elevated atmospheric CO2 on forests ([5], [34], [6], [19], [23]). Ceulemans et al. ([6]) argue that the question is not so much by what we do not know, but rather how to best integrate our knowledge in order to predict the performance and productivity of future ecosystems to global climatic changes. Newman et al. ([29]) have the opinion that our current ability to detect and predict changes in forest ecosystem productivity is constrained by several limitations. These include a poor understanding of belowground productivity, the short duration of most analyses, and a need for greater examination of species or community-specific variability in productivity studies. From studies to date, we know that the life-long above ground growth response of forest trees cannot be accurately predicted from short-term experiments ([30]). Karnosky ([19]) suggests long-term studies using free-air CO2 enrichment (FACE) technologies or forest stands around natural CO2 vents so as to increase the knowledge base on forest ecosystem responses to elevated atmospheric CO2. There is no doubt that FACE experiments can offer valuable information. However, there are some shortcomings with those experiments. First is the representativity. If the FACE experiments try to cover the whole range of forest ecosystems types, the cost will be tremendously high. The second is that FACE experiments will have a higher rate of CO2 enrichment than the actual rising rate of CO2. Forest stands around natural CO2 vents are rather limited. The establishment of new plots in natural atmosphere has, of course, the disadvantage of the very long-term expectancy of conclusions. Hopefully, there are already experimental plots, which have a past of ecological measurements. These are the intensively monitored plots (800 in total) which were installed in Europe under the auspices of the ICP-Forests ([16]). Those plots were installed when concern about the threat of atmospheric pollution on forest vitality was widespread. In this work I will try to stress the importance of keeping monitoring these plots. More specifically, I will focus on the potential contribution the intensively monitored plots can offer to meet the knowledge gaps with regard to tree responses to elevated atmospheric CO2. These knowledge gaps were set by Karnosky ([19]). The measures suggested concern long-term monitoring so they must be as cost efficient as possible.

Tree growth 

It has been found that short-term assimilation of CO2 is significantly stimulated by increased CO2 in nearly all plant species ([34], [25]). However, in the longest study (25-30 years) of continuous exposure of forest trees to elevated atmospheric CO2 with forest stands of holm oak growing in the vicinity of two natural CO2 springs in Italy, it was found that the trees showed a moderate, age dependent increase in stem biomass production, but had significantly lower biomass of 6-year-old branches, decreased branching, and lower leaf area per unit branch biomass, compared to control trees at a nearby site ([13]). In the intensively monitored plots growth has been measured since 1995. At that time tree diameter was measured either with measuring tapes or calipers. Recently, during the Pan European FutMon project (⇒ http:/­/­www.­futmon.­org/­) some diameters were measured with girth bands. These bands are relatively cheap and very accurate. This kind of measurement can be extended in all plots to include many more trees. In some years there will be valuable results all over Europe.

Water balance 

Long-term studies of forest trees in an enriched atmosphere with CO2 have shown a significant 21% decrease in stomatal conductance ([26]). However, as tree biomass increases the question remains whether trees use more or less water even if stomatal conductance decreases. The installation of soil moisture sensors in many plots help in the calculation of the whole water balance in forest stands. The actual magnitude of transpiration cannot be calculated but a comparison between forest stands can be made. For instance, for the same amounts of rainfall and interception the stand with the less water loss in drainage (assuming there is no surface runoff) will have a higher transpiration rate. The soil water holding capacity of each stand will be a covariate in the statistical comparison.


An important aspect that has not been tackled so far by the ICP-Forests projects is the form of C in soils. Elevated atmospheric CO2 will bring about a stimulation of soil respiration, which can be much higher than the enhancement of root biomass ([4]). A major consequence of the increase in microbial activity and consequently in CO2 production is a potential negative effect on the accumulation of organic C in soils and thus C potential sequestration of soils ([15]). However, there is a plateau beyond which organic matter cannot be easily attacked by microbes. Mineralization of soil organic matter strongly depends on the size of the labile C pool in addition to the effects of the microbial community and abiotic environmental conditions like temperature and moisture ([7]). A simple method to measure the labile C pool in soils is by water extraction ([18]). Although water extractable organic C makes up only a small portion of total soil organic matter (usually less than 1% - [3]), it might provide a measure of microbially available C. Zhao et al. ([37]) found a strong relationship between water extractable organic C and the rates of C mineralization using arable and forest soils.

In the intensively monitored plots the two soil surveys have a distance of 10 years from each other (1997 and 2007). Most counties, if not all, have stored the samples so they can be reanalyzed. If a third survey takes place in another 10 years, there will be a set of data with the amount of microbially available C covering a time space of 30 years. Comparisons can be made having in mind a fourth or fifth survey for the next generations.

Plant nutrition and nutrient cycling  

The growth response of forest plants to the rising concentrations of CO2 depends on their ability to acquire soil nutrients and water ([12]). Nutrient imbalances are reflected in foliar analysis. Every two years foliar analysis is carried out in all plots. A valuable data bank has been formed and should be enriched in the following years.

It has been well documented that the nitrogen level in the foliage of trees growing under elevated atmospheric CO2 generally decreases ([24]). As an example for repeated measures analyses, Fig. 1 shows N concentrations in fir foliage over time in one of the intensively monitored plots in Greece ([28]). In that particular case no significant changes were observed.

Fig. 1 - Nitrogen concentration in current year’s needles of fir (Abies borisii regis) in Greece.

Nitrogen concentrations also decrease in litterfall ([31]). By contrast to N concentration, the quantity of litterfall increases 20-30% under elevated CO2 ([9]). It is not known how nutrient mineralization will change due to the higher quantity of CO2 in soil. In the intensively monitored plots litterfall is monitored. Litterfall quantities are measured and elemental analyses are carried out. A simple test is a time series comparison between the successive N concentrations in foliage and foliar litterfall.

If the N content in litterfall decreases so must decrease the litter decomposition rates and the N mineralization rates. Both of them can be measured with the classic method of the litterbags technique. This is a relatively easy technique that can be employed in the future.

Belowground carbon allocation 

Allocation of C to belowground plant structures often equals or exceeds aboveground litterfall C and aboveground respiration in forest ecosystems, making it the single most important fate for gross primary productivity ([20]). Despite its importance, total belowground allocation (TBCA) remains poorly quantified because it is difficult to quantify root and mycorrhizal processes by any method ([11], [14]). If growth is enhanced, there will be more C input into the soil. Therefore, a major indirect response to an increase in atmospheric CO2 consists in the greater below-ground C allocation through root exudation and turnover, which is likely to lead to changes in the size and the activity of soil microflora ([22]).

In the absence of direct measurements of TBCA, Raich & Nadelhoffer ([33]) and Davidson et al. ([8]) proposed the following equation (eqn. 1):

TBCA = Soil respiration C - Aboveground Litterfall C

where soil respiration is the sum of root respiration, root litter C decomposition and aboveground litter C decomposition.

A critical assumption of this approach to estimate TBCA is that that the ecosystem is at a steady state, which means that the annual inputs of C below ground are equal to annual rates of decomposition.

If the system is not at a steady state the previous equation becomes (eqn. 2):

TBCA = Rsoil - Clitterfall + ΔClitter + ΔCsoil + ΔCroot + Cexport

where ΔCsoil, ΔClitter, ΔCroot are the changes in C stocks of mineral soil, forest floor and root biomass, respectively, and Cexport is C loss through leaching. From the above equation the parameters Rsoil, Clitterfall and Cexport in soil solution can be measured continuously in the intensively monitored plots. ΔCsoil and ΔClitter can be measured in the following soil survey and compared with the survey in 2007. ΔCroot can be calculated from an equation between ABD (aboveground biomass density) in Mg ha-1 and RBD (root biomass density) also in Mg ha-1.

Cairns et al. ([2]) used the following equation (eqn. 3):

RBD = e-1085 0.926 ln (ABD)

The above equation was based on 160 studies covering tropical temperate and boreal forests. The use of this equation is encouraged by other workers ([1]).

The total above ground biomass includes foliage apart from woody biomass. There are equations connecting foliage and tree diameters and heights for the main forest species ([21]), so that all components of the equation can be found.

In order to apply the above equations, the soil respiration rates have to be measured. It is probably the only expensive measurement, but it will help in drawing valuable conclusions, as soil respiration depends on soil moisture and temperature repeated measures have to be taken in time and space. Vincent et al. ([35]) used soil respiration chambers on which a portable infrared gas analyser was connected. They measured respiration in daytime during the growth period in a temperate deciduous forest. Raich ([32]) measured soil respiration with the soda-lime technique in three Hawaiian rain forests in a whole year period. The soil respiration fluxes should be expressed as the littefall fluxes, i.e., in kg ha-1 yr-1. So a whole year of measurements is necessary. The number of samplers (chambers) depends on the variability of respiration rates and the required probability level. A trial can be carried out with a limited number of samplers after which the required sample size for a given confidence interval can be calculated according to statistical formulas ([36]).

In my opinion, the first simpler equation may be used in most cases and the second one may be applied when there is a third soil survey in the intensively monitored plots.


Phenology is the study of the periodicity of leafing, flowering and fruiting in plants in relation to climate and other environmental factors. There is the hypothesis that elevated CO2 can affect development of leaf area in the spring so that trees could potentially benefit from an earlier onset of C assimilation at the start of the growing season. This could be an important factor in the expansion of tree populations into areas currently too cold for their growth ([34]). Phenological observations are carried out regularly in the intensively monitored plots and if leaf area increases that will be written down. What I now suggest is the extension of phenological observations to mycorrhizal fungi. This is crucial because the plants’s ability to acquire soil resources in an elevated CO2 environment is mediated by symbiotic associations with mycorrhizal fungi. A new distribution of mycorrhizal fungi may not be beneficial to plants as the plant-fungi symbiosis was evolved over time due to natural selection.


The intensively monitored plot can be a valuable tool in assessing the impact of elevated CO2 on forests. The activities already existing should be complemented by the following actions:

  1. Tree growth is suggested to be monitored with girth band in all plots;
  2. A third soil survey must be carried out. In this survey, together with stored samples of the previous ones, the labile C should be determined by water extraction.
  3. Soil respiration must be measured so as to draw conclusions on the C allocated belowground.
  4. Organic matter mineralization rates should be determined in all plots.
  5. Phenology observations must include the distribution of mycorrhizal fungi.


Brown S (2002). Measuring carbon in forests: current status and future challenges. Environmental Pollution 116: 363-372.
::CrossRef::Google Scholar::
Cairns MA, Brown S, Helmer EH, Baumgardner GA (1997). Root biomass allocation in the world’s upland forests. Oecologia 111: 1-11.
::CrossRef::Google Scholar::
Chantigny MH (2003). Dissolved and water-extractable organic matter in soils: a review on the influence of land use and management practice. Geoderma 113: 357-380.
::CrossRef::Google Scholar::
Cheng WX, Johnson DW (1998). Elevated CO2, rhizosphere processes, and soil organic matter decomposition. Plant and Soil 202: 167-174.
::CrossRef::Google Scholar::
Ceulemans R, Mouseau M (1994). Effects of elevated atmospheric CO2 on woody plants. New Phytologist 127: 425-446.
::CrossRef::Google Scholar::
Ceulemans R, Janssens IA, Jach ME (1999). Effects of CO2 enrichment on trees and forests: Lessons to be learned in view of future ecosystems studies. Annals of Botany 84: 577-590.
::CrossRef::Google Scholar::
Davidson EA, Belk E, Boone RD (1998). Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest. Global Change Biology 4: 217-227.
::CrossRef::Google Scholar::
Davidson EA, Savage K, Bolstad P, Clark DA, Curtis PS, Ellsworth DS, Hanson PJ, Law BE, Luo Y, Pregitzer KS, Randolph JC, Zak D (2002). Belowground carbon allocation in forests estimated from litterfall and IRGA-based soil respiration measurements. Agricultural and Forest Meteorology 113: 39-51.
::CrossRef::Google Scholar::
De Lucia EH (1999). Net primary production of a forest ecosystem with experimental CO2 enrichment. Science 284 (5417): 1177-1179.
::CrossRef::Google Scholar::
Dixon RK, Brown S, Houghton RA, Solomon AM, Trexler MC, Wisnieski J (1994). Carbon pools and flux of global forest ecosystems. Science 263: 185-190.
::CrossRef::Google Scholar::
Hanson PJ, Edwards NT, Garten CT, Andrews JA (2000). Separating root and soil microbial contributions to soil respiration: a review of methods and observations. Biogeochemistry 48: 115-146.
::CrossRef::Google Scholar::
Hättenschwiler S, Körner C (1996). System-level adjustment to elevated CO2 in model spruce ecosystems. Global Change Biology 2: 377-387.
::CrossRef::Google Scholar::
Hättenschwiler S, Miglietta F, Raschi A, Körner C (1997). Morphological adjustment of mature Quercus ilex trees to elevated CO2. Acta Oecologica 18: 361-365.
::CrossRef::Google Scholar::
Hendrick RL, Pregitzer KS (1993). The dynamics of fine root length, biomass and nitrogen content in two northern hardwood ecosystems. Canadian Journal of Forest Research 23: 2507-2520.
::CrossRef::Google Scholar::
Hungate BA, Dukes JS, Shaw MR, Luo Y, Field CB (2003). Atmospheric science: nitrogen and climate change. Science 302: 1512-1513.
::CrossRef::Google Scholar::
ICP-Forests (2010). ICP-Forests: International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests.
::Online::Google Scholar::
IPCC (2001). Climate change: the scientific basis. Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.
::Google Scholar::
Jiang PK, Xu QF (2006). Abundance and dynamics of soil labile carbon pools under different types of forest vegetation. Pedosphere 16: 505-511.
::CrossRef::Google Scholar::
Karnosky DF (2003). Impacts of elevated CO2 on forest trees and forest ecosystems: knowledge gaps. Environment International 29: 161-169.
::CrossRef::Google Scholar::
Kimmins JP (1996). Forest ecology. A foundation for sustainable management. Prentice Hall, New Jersey, USA.
::Google Scholar::
Kittredge JM, Rimmer JH, Looney MA (1994). Validation of the rockport fitness walking test for adults with mental retardation. Med Sci Sports Exerc 26 (1): 95-102.
::Online::Google Scholar::
Körner C (2000). Biosphere responses to CO2 enrichment. Ecological Applications 10: 1590-1619.
::CrossRef::Google Scholar::
Lal R (2005). Forest soils and carbon sequestration. Forest Ecology and Management 220: 242-258.
::CrossRef::Google Scholar::
Lindroth RL, Kinney KK, Platz CL (1993). Responses of deciduous trees to elevated atmospheric CO2: productivity, phytochemistry and insect performance. Ecology 74: 763-777.
::CrossRef::Google Scholar::
Luo Y, Reynolds J, Wang YP, Wolfe D (1999). Research for predictive understanding of plant responses to elevated CO2. Global Change Biology 5: 143-156.
::CrossRef::Google Scholar::
Medlyn BE, Barton CMV, Broadmeadow MSI, Ceulemans R, De Angelis P, Forestreuter M, et al. (2001). Stomatal conductance of forest species after long-term exposure to elevated CO2 concentrations: a synthesis. New Phytologist 149: 247-264.
::CrossRef::Google Scholar::
Melillo JM, McGuire DA, Kicklighter DW, Moore B, Vorosmarty CJ, Schloss AL (1993). Global climate change and terrestrial net primary production. Nature 363: 234-240.
::CrossRef::Google Scholar::
Michopoulos P, Economou A, Karetsos G, Tsagari K, Voulala M, Bourletsikas A, Kaoukis, K (2010). Nitrogen in a fir stand. Is there any risk of saturation? 13th Greek Soil Science Congress, pp. 389-397. [In Greek with an english abstract].
::Google Scholar::
Newman GS, Arthur MA, Muller RN (2006). Above and below ground net primary production in a temperate mixed deciduous forest. Ecosystems 9: 317-329.
::CrossRef::Google Scholar::
Norby RJ, Wullschleger SD, Gunderson CA, Johnson DW, Ceulemans R (1999). Tree responses to rising CO2 in field experiments: implications for the future forest. Plant Cell Environment 22: 683-714.
::CrossRef::Google Scholar::
Norby RJ, Cotrufo MF, Ineson P, O’Neil EG, Canadell JG (2001). Elevated CO2, litter chemistry, and decomposition: a synthesis. Oecologia 127: 153-165.
::CrossRef::Google Scholar::
Raich JW (1998). Aboveground productivity and soil respiration in three Hawaiian rain forests. Forest Ecology and Management 107: 309-318.
::CrossRef::Google Scholar::
Raich JW, Nadelhoffer KJ (1989). Belowground carbon allocation in forest ecosystems: global trends. Ecology 70: 1346-1354.
::CrossRef::Google Scholar::
Saxe H, Ellsworth DS, Heath J (1998). Tree and forest functioning in an enriched CO2 atmosphere. New Phytologist 139: 395-436.
::CrossRef::Google Scholar::
Vincent G, Shahriari AR, Lucot E, Badot PM, Epron D (2006). Spatial and seasonal variations in soil respiration in a temperate deciduous forest with fluctuating water table. Soil Biology and Biochemistry 38: 2527-2535.
::CrossRef::Google Scholar::
Weiss NA (1989). Elementary statistics. Addison-Wesley Publishing Company, Massachusetts, USA.
::Google Scholar::
Zhao M, Zhou J, Kalbitz K (2008). Carbon mineralization and properties of water-extractable organic carbon in soils of the south Loess Plateau in China. European Journal of Soil Biology 44: 158-165.
::CrossRef::Google Scholar::


Michopoulos P (2011).
Effects of increasing CO2 on trees and intensively monitored plots: research needs in view of future ecosystem studies
iForest - Biogeosciences and Forestry 4: 172-175. - doi: 10.3832/ifor0590-004
First Previous Next Last
© iForest

Download Reference

Paper ID# ifor0590-004
Title Effects of increasing CO2 on trees and intensively monitored plots: research needs in view of future ecosystem studies
Authors Michopoulos P
Close Download