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Swiss National Forest Inventory (NFI) produces estimates of characteristics related to the state and change of the forest resources in the whole country as well as in smaller regions and domains. The estimates are based on measurements on permanent field plots placed on a systematic grid over the country. Digital stereo aerial images are an important source of auxiliary information that can be used with post-stratified estimation to increase the precision of the estimates. We examined post-stratification based on stereo image information, available on a much denser grid than the field plots, for the estimation of forest area, total growing-stock volume and growing-stock volume per unit of accessible forest area. We considered 31 post-stratification schemes that consisted of (1) forest/non-forest stratification by four alternative methods based on manual or semi-automated stereo image interpretation, and (2) sub-stratification within the forest stratum by regression-tree models constructed between field-measured growing-stock volume and stereo-image-retrieved vegetation height characteristics. We applied the schemes in two real NFI estimation cycles, and found that the most precise schemes reduced the variance of the whole-country estimators of forest area, total growing-stock volume and growing-stock volume per unit of accessible forest area by 81%, 67% and 34%, respectively, compared to the estimator without post-stratification. Based on this study, we consider regression-tree modelling well-suited for post-stratification, as it produces stratum boundaries as a direct result of modelling, appears robust against deviating values in fitting data, and avoids problems with unrealistic model predictions in application.

Self-thinning dynamics are often considered when managing stand density in forests and are used to constrain forest growth models. However, self-thinning relationships are often quantified using only data at a conceptualised self-thinning line, even though self-thinning can begin before the stand actually reaches a self-thinning line. Also, few self-thinning relationships account for the effects of species composition in mixed-species forests, and stand structure such as relative height of species (in mixtures), and/or size or age cohorts in uneven-aged forests. Such considerations may be important given the effects of global climate change and interest in mixed-species and uneven-aged forests. The objective of this study was to develop self-thinning relationships based on changes in the tree density relative to mean tree diameter, instead of focusing only on data for state variables (e.g. tree density) at the self-thinning line. This was done while also considering how the change in tree density is influenced by site quality and stand structure (species composition and relative height). The relationships were modelled using data from temperate Australian Eucalyptus plantations (436 plots), subtropical forests in China (88 plots), and temperate forests in Switzerland (1055 plots). Zero-inflated and hurdle generalized linear models with Poisson and negative binomial distributions were fit for several species, as well as for all-species equations. The intercepts and slopes of the self-thinning lines were higher than many published studies which may have resulted from both the less restrictive equation form and data selection. The rates of self-thinning often decreased as the proportion of the object species increased, as relative height increased (species or size cohort became more dominant), and as site (quality) index increased. The effects of aridity varied between species, with self-thinning increasing with aridity index for Abies alba, Pinus sylvestris, Quercus petraea and Quercus robur, but decreasing with aridity index for Eucalyptus nitens, Fagus sylvatica and Picea abies as sites became wetter and cooler. Self-thinning model parameters were not correlated with species traits, including specific leaf area, wood basic density or crown diameter – stem diameter allometry. All-species self-thinning relationships based on all data could be adjusted using a correction factor for rarer species where there were insufficient data to develop species-specific equations. The approach and equations developed could be used in forest growth models to calculate how the tree density declines as mean tree size increases, as height changes relative to other cohorts or species, as species proportions change, and as climatic and edaphic conditions change.

In forestry, site productivity is commonly described using the concept of site index (SI) and its effect on the potential mean annual increment. Although a unified causal explanation between SI and productivity is still missing, operational methods have been developed to determine SI on the basis of the existing tree crop or other indirect indicators of environmental drivers. In ecology, progress has been made in deriving productivity from the carbon balance, including photosynthesis, respiration and tissue longevity, but considerable gaps remain in quantifying the impact of soil processes on below-ground carbon allocation which would be crucial for closure of the total carbon balance. Recent empirical studies in Finland have found significant and consistent differences in the foliage to fine-root ratio and fine-root lifetime between the conventional SI based on field layer vegetation in geographical vegetation zones. In this study, we utilised this information to bridge the gap between the large body of empirical information on SI and productivity, and productivity as derived from the carbon balance. We incorporated assumptions concerning the climate and soil response of the carbon balance components in a process-based model, PipeQual, and applied the approach to Norway spruce stands in Fenno–Scandian conditions. The results agreed well with an empirical growth and yield model and provided fairly accurate projections for two contrasting test sites. The study provided insights into the role of the component processes of productivity. Importantly, the north-south gradient of productivity was equally attributed to a northward decrease in temperature and an increase in carbon allocation to fine roots. This cautions against climate change projections on the basis of current growth variation with temperature and calls for improved mechanistic models incorporating plant, soil and microbial interactions in regulating the soil-forest carbon and nitrogen fluxes.

The photochemical reflectance index (PRI) is regarded as a promising proxy to track the dynamics of photosynthetic light use efficiency (LUE) via remote sensing. The implementation of this approach requires the relationship between PRI and LUE to scale not only in space but also in time. The short-term relationship between PRI and LUE is well known and is based on the regulative process of non-photochemical quenching (NPQ), but at the seasonal timescale the mechanisms behind the relationship remain unclear. We examined to what extent sustained forms of NPQ, photoinhibition of reaction centres, seasonal changes in leaf pigment concentrations, or adjustments in the capacity of alternative energy sinks affect the seasonal relationship between PRI and LUE during the year in needles of boreal Scots pine. PRI and NPQ were highly correlated during most of the year but decoupled in early spring when the foliage was deeply downregulated. This phenomenon was attributed to differences in the physiological mechanisms controlling the seasonal dynamics of PRI and NPQ. Seasonal adjustments in the pool size of the xanthophyll cycle pigments, on a chlorophyll basis, controlled the dynamics of PRI, whereas the xanthophyll de-epoxidation status and other xanthophyll-independent mechanisms controlled the dynamics of NPQ at the seasonal timescale. We conclude that the PRI leads to an underestimation of NPQ, and consequently overestimation of LUE, under conditions of severe stress in overwintering Scots pine, and most likely also in species experiencing severe drought. This severe stress-induced decoupling may challenge the implementation of the PRI approach.

The maximum light use efficiency (LUE = gross primary production (GPP)/absorbed photosynthetic photon flux density (aPPFD)) of plant canopies has been reported to vary spatially and some of this variation has previously been attributed to plant species differences. The canopy nitrogen concentration [N] can potentially explain some of this spatial variation. However, the current paradigm of the N-effect on photosynthesis is largely based on the relationship between photosynthetic capacity (A(max)) and [N], i.e., the effects of [N] on photosynthesis rates appear under high PPFD. A maximum LUE-[N] relationship, if it existed, would influence photosynthesis in the whole range of PPFD. We estimated maximum LUE for 14 eddy-covariance forest sites, examined its [N] dependency and investigated how the [N]-maximum LUE dependency could be incorporated into a GPP model. In the model, maximum LUE corresponds to LUE under optimal environmental conditions before light saturation takes place (the slope of GPP vs. PPFD under low PPFD). Maximum LUE was higher in deciduous/mixed than in coniferous sites, and correlated significantly with canopy mean [N]. Correlations between maximum LUE and canopy [N] existed regardless of daily PPFD, although we expected the correlation to disappear under low PPFD when LUE was also highest. Despite these correlations, including [N] in the model of GPP only marginally decreased the root mean squared error. Our results suggest that maximum LUE correlates linearly with canopy [N], but that a larger body of data is required before we can include this relationship into a GPP model. Gross primary production will therefore positively correlate with [N] already at low PPFD, and not only at high PPFD as is suggested by the prevailing paradigm of leaf-level A(max)-[N] relationships. This finding has consequences for modelling GPP driven by temporal changes or spatial variation in canopy [N].

Transplanting recovery of urban trees is an essential first step in their acclimation from nursery to challenging urban growing sites. Changes in crown allometry during this period are not well known. We followed annual shoot extension, crown structure and leaf area of Alnus glutinosa and Tilia × vulgaris street trees for six years from transplanting into their growing site. The growing site of Tilia trees suffered from excessive soil moisture whereas the Alnus site was more normal regarding soil water relations with periods of drought. The transplanting recovery of Tilia trees was delayed due to the deleterious influence of excessive soil water, but Alnus trees recovered substantially within the first 2–3 years. Leaf area in relation to branch basal area changed throughout the research period, indicating tree adaptation to new growing conditions.

We compared the CO2 exchange and its controls in the plant communities of a strongly patterned aapa mire, the Kaamanen fen in northern Finland. Based on a systematic vegetation inventory and an ordination analysis, four plant community types were chosen for the study: Ericales–Pleurozium string tops, Betula–Sphagnum string margins, Trichophorum tussock flarks and Carex–Scorpidium wet flarks. We measured plant community CO2 exchange with a closed chamber technique during the growing season of 2007 and early summer of 2008. Nonlinear regression models were used for simulating the CO2 exchange over the measurement period for different mire components and for the whole mire. The CO2 exchange dynamics distinguished two functional components in the mire: an ombrotrophic component (Ericales–Pleurozium string tops) and a minerotrophic component (other plant community types). Minerotrophic plant communities responded similarly to environmental controls, the most important of these being variation in leaf area and aerobic peat volume (water level). The ombrotrophic component dynamics were more obscure; frost and possibly peat moisture played a role. The minerotrophic communities functioned as effective CO2 sinks in the simulation, while the net CO2 exchange of the ombrotrophic community was close to zero. The smaller NEE of the ombrotrophic community was due to less efficient photosynthesis per unit leaf area in combination with high ecosystem respiration resulting from a large aerobic peat volume. Our study shows that a fen/bog functional dichotomy can also exist within one mire. Wet minerotrophic communities within northern mires can act as effective CO2 sinks.

In this study we introduce and test a new simple approach for estimating annual stand-level gross primary production (GPP), net primary production (NPP) and stem biomass growth based on carbon acquisition and allocation, by combining existing summary models. The focus is on the variation of GPP and NPP across different parts of Finland caused by climate. A summary model for estimating light-use efficiency is applied to calculate the annual GPP of a fully closed canopy ( P 0 ) for different sites as a function of climatic conditions. The site-specific P 0 s are first determined for five sites using long-term series of daily weather data from the Finnish Meteorological Institute (FMI), and these results are further generalised to all sites using effective temperature sum (ETS) as a predictor. Actual canopy GPP is calculated as a fraction of the estimated site-specific P 0 using a summary model of the effect of shading on photosynthesis in non-homogeneous forests. Leaf area is estimated from measured tree data using the pipe model. NPP:GPP ratio is estimated on the stratum level from mean height. The allocation to stem growth is estimated from stand age and site type, using a summary equation based on results from earlier studies. The method was tested against data from permanent sample plots of the Finnish National Forest Inventory (NFI) from years 1985 and 1995. The results indicate that the approach produces realistic short-term estimations for stem growth. At the stand level the model was nearly unbiased (2.1% underestimation), with RMSE of 34% and R 2 of 0.52, and it provided a clearly better fit than a simple linear prediction of stem growth from the estimated GPP. More importantly, we showed in a model comparison that in the present data set our model provided results of similar accuracy as a well-established empirical tree-level growth model.

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems. DOI: http://dx.doi.org/10.7554/eLife.14093.001, eLife digest Plants grow throughout their lifetime, forming new flowers and leaves at the tips of their stems through a patterning process called phyllotaxis, which occurs in spirals for a vast number of plant species. The classical view suggests that the positioning of each new leaf or flower bud at the tip of a growing stem is based on a small set of principles. This includes the idea that buds produce inhibitory signals that prevent other buds from forming too close to each other. When computational models of phyllotaxis follow these ‘deterministic’ principles, they are able to recreate the spiral pattern the buds form on a growing stem. In real plants, however, the spiral pattern is not always perfect. The observed disturbances in the pattern are believed to reflect the presence of random fluctuations – regarded as noise – in phyllotaxis. Here, using numerical simulations, Refahi et al. noticed that the patterns of inhibitory signals in a shoot tip pre-determine the locations of several competing sites where buds could form in a robust manner. However, random fluctuations in the way cells perceive these inhibitory signals could greatly disturb the timing of organ formation and affect phyllotaxis patterns. Building on this, Refahi et al. created a new computational model of bud patterning that takes into account some randomness in how cells perceive the inhibitory signals released by existing buds. The model can accurately recreate the classical spiral patterns of buds and also produces occasional disrupted patterns that are similar to those seen in real plants. Unexpectedly, Refahi et al. show that these ‘errors’ reveal key information about how the signals that control phyllotaxis might work. These findings open up new avenues of research into the role of noise in phyllotaxis. The model can be used to predict how altering the activities of genes or varying plant growth conditions might disturb this patterning process. Furthermore, the work highlights how the structure of disturbances in a biological system can shed new light on how the system works. DOI: http://dx.doi.org/10.7554/eLife.14093.002

This paper develops a statistical model for daily gross primary production (GPP) in boreal and temperate coniferous forests. The model applies the light use efficiency (LUE) approach, which estimates the conversion efficiency of daily absorbed photosynthetically active radiation (APAR) into daily GPP as a product of potential LUE and modifying factors. The latter were derived from daily total APAR and daily mean temperature, vapour pressure deficit (VPD) and soil water content (SWC). Modelling data came from five European eddy covariance measurement towers over 2-8 years. The model was tested against independent data from two AmeriFlux stations. The model with the APAR, temperature and VPD modifiers worked well in almost all the site-year combinations, but the SWC modifier only improved the fit in few cases. Geographical variation was found in the modifiers and potential LUE in site-specific models. When a model was fitted to pooled data, differences between sites could be explained by potential LUE, leaf area and environmental conditions. The test against the AmeriFlux data corroborated this finding. The potential LUE varied from 1.9 to 3.1 g C MJ(-1), and a weak correlation was found between foliar nitrogen concentration and potential LUE. Some year-to-year variation remained which could be captured by neither the pooled nor the site-specific models. (Less)

The metabolic and physical processes result in concentration, pressure and temperature differences that generate fluxes within ecosystems and between ecosystems and their surroundings. We apply the same approach combining metabolic and physical processes with transport in the analysis of very different phenomena from water and sugar transport within trees to the fluxes of carbon and nutrients in the forest ecosystem.

In the common methods of forest mensuration, including stem volume models and Bitterlich sampling, stem cross-sections are assumed to be circular. In nature this assumption is never exactly fulfilled. Errors due to non-circularity have been presumed to be small and unimportant but studied little: theoretical and empirical studies exist on cross-section area estimation, but errors in stem volume estimation have not been investigated at all, and errors in Bitterlich sampling are theoretically known only for stand basal area estimation. In the theoretical part of this study, we developed methods for quantifying the systematic and sampling errors that 22 common ways of selecting diameter within non-circular cross-sections induce (i) in area estimates by the circle area formula, (ii) in stand total estimates by Bitterlich sampling, and (iii) in stem volume estimates by a volume equation, by a cubic-spline-interpolated stem curve, and by a generalised volume estimator. In the empirical part, based on the digital images of 709 discs taken at 6–10 heights in 81 Scots pine stems from different parts of Finland, we investigated the variation in cross-section shape, and demonstrated the magnitude of the errors presented in the theoretical part. We found that non-circularity causes systematic overestimation of area and volume, and inflicts potentially systematic error on stand total estimates by Bitterlich sampling. In our data these effects were small, but the finding is not generalisable due the skewed size distribution and poor geographical representativeness of the data. We recommend using diameter derived from girth for both tree and stand level estimation, as it involves no sampling error and produces clearly the most stable systematic errors.

International audience; Gross primary production (GPP) is the primary source of all carbon fluxes in the ecosystem. Understanding variation in this flux is vital to understanding variation in the carbon sink of forest ecosystems, and this would serve as input to forest production models. Using GPP derived from eddy-covariance (EC) measurements, it is now possible to determine the most important factor to scale GPP across sites. We use long-term EC measurements for six coniferous forest stands in Europe, for a total of 25 site-years, located on a gradient between southern France and northern Finland. Eddy-derived GPP varied threefold across the six sites, peak ecosystem leaf area index (LAI) (all-sided) varied from 4 to 22 m2 m-2 and mean annual temperature varied from -1 to 13C. A process-based model operating at a half-hourly time-step was parameterized with available information for each site, and explained 71-96% in variation between daily totals of GPP within site-years and 62% of annual total GPP across site-years. Using the parameterized model, we performed two simulation experiments: weather datasets were interchanged between sites, so that the model was used to predict GPP at some site using data from either a different year or a different site. The resulting bias in GPP prediction was related to several aggregated weather variables and was found to be closely related to the change in the effective temperature sum or mean annual temperature. High R 2s resulted even when using weather datasets from unrelated sites, providing a cautionary note on the interpretation of R 2 in model comparisons. A second experiment interchanged stand-structure information between sites, and the resulting bias was strongly related to the difference in LAI, or the difference in integrated absorbed light. Across the six sites, variation in mean annual temperature had more effect on simulated GPP than the variation in LAI, but both were important determinants of GPP. A sensitivity analysis of leaf physiology parameters showed that the quantum yield was the most influential parameter on annual GPP, followed by a parameter controlling the seasonality of photosynthesis and photosynthetic capacity. Overall, the results are promising for the development of a parsimonious model of GPP.

Our purpose was to develop a FTIR spectroscopic method to be used to determine the lignin content in a large number of samples and to apply this method studying variation in sapwood and heartwood lignin content between three fast-growing cutting clones grown in three sites. Models were estimated with 18 samples and tested with 6 samples for which the Klason lignin + acid soluble lignin content had been determined. Altogether 272 candidate models were built with all-subset regressions from the principal components estimated from differently treated transmission spectra of the samples; the spectra were recorded on KBr pellets of sieved and unsieved unextracted wood powder and subjected to four different preprocessings and two different wavenumber selection schemes. The final model showed an adequate fit in the estimation data (R = 0.74) as well as a good prediction performance in the test data (R = 0.90). This model was based on the wavenumber range of 1850–500 cm of the line-subtraction-normalised spectra recorded from sieved samples. The model was used to predict lignin content in 64 samples of the same material. One of the clones had a slightly lower sapwood lignin content than the two other clones. The fertile growing site with fast growing trees showed slightly higher sapwood lignin content compared with the other two sites. The model was also used to predict the lignin content in the earlywood of 45 individual annual rings. Variation between individual stems and between annual rings was found to be large. No correlation was found between the lignin content and density of earlywood.22P–1

Simple approaches to predicting ecosystem fluxes are useful in large-scale applications because existing data rarely support justified use of complex models. We developed a model of daily ecosystem gross primary production (P), evapotranspiration (E), and soil water content (theta), which only requires standard weather data and information about the fraction of absorbed radiation. We estimated the parameters of the model for two boreal Scots pine eddy-covariance sites (Hyytiala and Sodankyla). The model predicted P and E adequately for Hyytiala for both calibration and additional test years. The model calibrated for Hyytiala slightly overestimated P and E in Sodankyla, but its performance levelled with the model calibrated for Sodankyla in a dry year. Sensitivity analysis of the model implied that drought prediction is sensitive, not only to key E submodel parameters, but also to P submodel parameters. Further improvement and calibrations of the model could benefit from forest sites with varying canopy and different species structures.