Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

    Current refinement(s):

    Records 1 - 20 / 43

    • help
    • print

      Print search results

    • export

      Export search results

    Check title to add to marked list
    Monitoring spring phenology with high temporal resolution terrestrial LiDAR measurements
    Calders, K. ; Schenkels, T. ; Bartholomeus, H.M. ; Armston, J. ; Verbesselt, J. ; Herold, M. - \ 2015
    Agricultural and Forest Meteorology 203 (2015). - ISSN 0168-1923 - p. 158 - 168.
    leaf-area index - pulsed-laser systems - canopy gap fraction - temperate forest - deciduous forest - climate-change - part i - profiles - environments - photography
    Vegetation phenology studies the timing of recurring seasonal dynamics and can be monitored through estimates of plant area index (PAI). Shifts in spring phenology are a key indicator for the effect of climate change, in particular the start of the growing season of forests. Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, is an active remote sensing technique and measures the forest structure with high spatial detail and accuracy. TLS provides information about the 3D distribution of canopy constituents and vertical plant profiles can be derived from these data. Vertical plant profiles describe the plant area per unit volume as a function of height, and can be used to used to monitor seasonal dynamics through PAI. Here, we present a TLS time series based on 48 measurement days of four sampling locations in a deciduous forest in the Netherlands. Vertical plant profiles are derived for each measurement and allow us to quantify not only total canopy integrated PAI, but also monitor PAI at specific horizontal layers. Sigmoidal models show a good fit to the derived total canopy integrated PAI time series (CV(RMSE) 0.99). The start of season (SOS) based on these models occurs between March 29 and April 3, 2014, depending on the species composition. The SOS derived from the TLS data corresponds well with field observations and occurs 7–12 days earlier compared to the SOS estimate from the MODIS NDVI time series. This is mainly caused by the lower relative standard deviation for TLS measurements in leaf-off conditions (0.72% compared to 2.87% for the MODIS NDVI data), which allows us to significantly detect small changes in phenology earlier. TLS allows us to monitor PAI at specific horizontal layers and we defined an understorey, intermediate and upper canopy layer. Even though our study area had only a sparse understorey, small differences are observed in the SOS between the different layers. We expect that these phenological differences will be more pronounced in multi-layered forests and TLS shows the potential to study seasonal dynamics not only as a function of time, but also as a function of canopy height.
    A model-based approach to studying changes in compositional heterogeneity
    Baeten, L. ; Warton, D. ; Calster, H. van; Frenne, P. De; Verstraeten, G. ; Bonte, D. ; Bernhardt-Romermann, M. ; Cornelis, R. ; Decocq, G. ; Eriksson, O. ; Hommel, P.W.F.M. - \ 2014
    Methods in Ecology and Evolution 5 (2014)2. - ISSN 2041-210X - p. 156 - 164.
    with-standards forest - biotic homogenization - beta-diversity - plant-communities - deciduous forest - vegetation - turnover - dissimilarity - nestedness - dispersion
    1. Non-random species loss and gain in local communities change the compositional heterogeneity between communities over time, which is traditionally quantified with dissimilarity-based approaches. Yet, dissimilarities summarize the multivariate species data into a univariate index and obscure the species-level patterns of change, which are central to understand the causes and consequences of the community changes. 2. Here, we propose a model-based approach that looks for species-level effects of time period and construct a multiple-site metric as a sum across species to test the consistency of the individual species responses. Species fall into different response types, showing how they influence the changes in community heterogeneity. 3. In a comparison with other multiple-sitemetrics, we illustrate the properties of our method and the differences and similarities with other approaches. For instance, ourmetric estimates the total variation in a community data set based on species-level contributions, not the compositional dissimilarities between particular sites. Similar to some other approaches, we can distinguish between heterogeneity derived from turnover or richness differences. 4. Our approach was applied to a set of 23 forest understorey resurvey studies spread across Europe. We show the species gains and lossesmay as well decrease or increase levels of community heterogeneity. Although species occurrences and communities have not changed in a consistent way along continental-scale environmental gradients such as climatic conditions, several species shifted in a similar way across the different data sets. 5. Testing the significance of shifts in species prevalence over time to infer corresponding changes in the compositional heterogeneity among sites provides a very intuitive tool for community resurvey studies. The main strengths of our framework are the explicit consideration of the relative roles of species gains and losses and the straightforward generalization to different sets of hypotheses related to community changes. Key-words: biodiversity, community composition, biotic homogenization, binomial deviance, dissimilarity, beta diversity,multivariate analysis,meta-analysis, forest understorey
    Enhancement of crop photosynthesis by diffuse light: quantifying the contributing factors
    Li, T. ; Heuvelink, E. ; Dueck, T.A. ; Janse, J. ; Gort, G. ; Marcelis, L.F.M. - \ 2014
    Annals of Botany 114 (2014)1. - ISSN 0305-7364 - p. 145 - 156.
    modeling canopy photosynthesis - net ecosystem exchange - structural plant-model - chlorophyll fluorescence - deciduous forest - global radiation - direct component - solar-radiation - leaf-area - leaves
    Plants use diffuse light more efficiently than direct light. However, experimental comparisons between diffuse and direct light have been obscured by co-occurring differences in environmental conditions (e.g. light intensity). This study aims to analyse the factors that contribute to an increase in crop photosynthesis in diffuse light and to quantify their relative contribution under different levels of diffuseness at similar light intensities. The hypothesis is that the enhancement of crop photosynthesis in diffuse light results not only from the direct effects of more uniform vertical and horizontal light distribution in the crop canopy, but also from crop physiological and morphological acclimation. Tomato (Solanum lycopersicum) crops were grown in three greenhouse compartments that were covered by glass with different degrees of light diffuseness (0, 45 and 71 % of the direct light being converted into diffuse light) while maintaining similar light transmission. Measurements of horizontal and vertical photosynthetic photon flux density (PPFD) distribution in the crop, leaf photosynthesis light response curves and leaf area index (LAI) were used to quantify each factor's contribution to an increase in crop photosynthesis in diffuse light. In addition, leaf temperature, photoinhibition, and leaf biochemical and anatomical properties were studied. The highest degree of light diffuseness (71 %) increased the calculated crop photosynthesis by 7 center dot 2 %. This effect was mainly attributed to a more uniform horizontal (33 % of the total effect) and vertical PPFD distribution (21 %) in the crop. In addition, plants acclimated to the high level of diffuseness by gaining a higher photosynthetic capacity of leaves in the middle of the crop and a higher LAI, which contributed 23 and 13 %, respectively, to the total increase in crop photosynthesis in diffuse light. Moreover, diffuse light resulted in lower leaf temperatures and less photoinhibition at the top of the canopy when global irradiance was high. Diffuse light enhanced crop photosynthesis. A more uniform horizontal PPFD distribution played the most important role in this enhancement, and a more uniform vertical PPFD distribution and higher leaf photosynthetic capacity contributed more to the enhancement of crop photosynthesis than did higher values of LAI.
    Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR
    Calders, K. ; Armston, J. ; Newnham, G. ; Herold, M. ; Goodwin, N. - \ 2014
    Agricultural and Forest Meteorology 194 (2014). - ISSN 0168-1923 - p. 104 - 117.
    ground-based lidar - pulsed-laser systems - wave-form lidar - tropical forests - deciduous forest - leaf-area - canopy - airborne - heterogeneity - environments
    The vertical distribution of plant constituents is a key parameter to describe vegetation structure and influences several processes, such as radiation interception, growth and habitat. Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, has the potential to measure the canopy structure with high spatial detail and accuracy. Vertical plant profiles, which describe the plant area per unit volume (PAVD) as a function of height, are often used to quantify the vertical structure. However, most studies do not account for topography, use registered multiple TLS scans or use a detailed airborne LiDAR digital terrain model to account for this variation in ground height. Airborne LiDAR is often not available or expensive to acquire. Here, we present an approach that facilitates rapid, robust and automated assessment of the vertical structure of vegetation. We use single scans and local plane fitting to correct for topographic effects in vertical plant profiles and test our approach in five different Australian forest types with different topography and understorey. We validate our approach with topography-corrected vertical plant profiles with digital terrain models derived from airborne LiDAR. Our results demonstrate that not correcting for topography can lead to significant errors in the vertical distribution of plant constituents (CV(RMSE) up to 66.2%, typically ranging from 4.2% to 13.8%). This error decreases significantly when topography is accounted for with TLS plane fitting (CV(RMSE) up to 20.6%, typically ranging from 1.5% to 12.6%). We demonstrate that height metrics from vertical plant profiles that are not corrected for topography depart significantly from those that are inferred from the reference profile. The effect is most noticeable for canopy top height and the peak PAVD height. Correcting topography with a TLS plane fitting approach reduces the error in canopy top height by at least 77% and up to 100%, and reduces the error in peak PAVD height by 83.3% and up to 100%. We also show the advantage of a multiple return over a first return TLS instrument. The definition of the ground returns with a first return instrument might be problematic in environments with dense herbaceous understorey and there is an overall trend of lower height metrics compared to multiple return instruments. We present a data-driven approach that is based on single scan TLS data. The latter is of importance for large area sampling as it allows more sites to be sampled from existing resources and facilitate consistent processing of archived TLS data, which is often single scan data with no survey control.
    Remote sensing of annual terrestrial gross primary productivity from MODIS: an assessment using the FLUXNET La Thuile data set
    Verma, M. ; Friedl, M.A. ; Richardson, A.D. ; Kiely, G. ; Cescatti, A. ; Law, B.E. ; Wohlfahrt, G. ; Gielen, G. ; Roupsard, O. ; Moors, E.J. - \ 2014
    Biogeosciences 11 (2014). - ISSN 1726-4170 - p. 2185 - 2200.
    net ecosystem exchange - carbon-dioxide exchange - use efficiency model - forests green-up - rain-fed maize - interannual variability - vegetation index - surface temperature - climatic controls - deciduous forest
    Gross primary productivity (GPP) is the largest and most variable component of the global terrestrial carbon cycle. Repeatable and accurate monitoring of terrestrial GPP is therefore critical for quantifying dynamics in regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is widely used to monitor and model spatiotemporal variability in ecosystem properties and processes that affect terrestrial GPP. We used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and FLUXNET to assess how well four metrics derived from remotely sensed vegetation indices (hereafter referred to as proxies) and six remote sensing-based models capture spatial and temporal variations in annual GPP. Specifically, we used the FLUXNET La Thuile data set, which includes several times more sites (144) and site years (422) than previous studies have used. Our results show that remotely sensed proxies and modeled GPP are able to capture significant spatial variation in mean annual GPP in every biome except croplands, but that the percentage of explained variance differed substantially across biomes (10–80%). The ability of remotely sensed proxies and models to explain interannual variability in GPP was even more limited. Remotely sensed proxies explained 40–60% of interannual variance in annual GPP in moisture-limited biomes, including grasslands and shrublands. However, none of the models or remotely sensed proxies explained statistically significant amounts of interannual variation in GPP in croplands, evergreen needleleaf forests, or deciduous broadleaf forests. Robust and repeatable characterization of spatiotemporal variability in carbon budgets is critically important and the carbon cycle science community is increasingly relying on remotely sensing data. Our analyses highlight the power of remote sensing-based models, but also provide bounds on the uncertainties associated with these models. Uncertainty in flux tower GPP, and difference between the footprints of MODIS pixels and flux tower measurements are acknowledged as unresolved challenges.
    Effects of ENSO and temporal rainfall variation on the dynamics of successional communities in old-field succession of a seasonal tropical dry forest
    Maza-Villalobos, S. ; Poorter, L. ; Martínez-Ramos, M. - \ 2013
    PLoS ONE 8 (2013). - ISSN 1932-6203 - 12 p.
    soil seed banks - deciduous forest - el-nino - carbohydrate storage - severe drought - woody-plants - land-use - tree - growth - climate
    The effects of temporal variation of rainfall on secondary succession of tropical dry ecosystems are poorly understood. We studied effects of inter-seasonal and inter-year rainfall variation on the dynamics of regenerative successional communities of a tropical dry forest in Mexico. We emphasized the effects caused by the severe El Niño Southern Oscillation (ENSO) occurred in 2005. We established permanent plots in sites representing a chronosequence of Pasture (abandoned pastures, 0–1 years fallow age), Early (3–5), Intermediate (8–12), and Old-Growth Forest categories (n = 3 per category). In total, 8210 shrubs and trees 10 to 100-cm height were identified, measured, and monitored over four years. Rates of plant recruitment, growth and mortality, and gain and loss of species were quantified per season (dry vs. rainy), year, and successional category, considering whole communities and separating seedlings from sprouts and shrubs from trees. Community rates changed with rainfall variation without almost any effect of successional stage. Mortality and species loss rates peaked during the ENSO year and the following year; however, after two rainy years mortality peaked in the rainy season. Such changes could result from the severe drought in the ENSO year, and of the outbreak of biotic agents during the following rainy years. Growth, recruitment and species gain rates were higher in the rainy season but they were significantly reduced after the ENSO year. Seedlings exhibited higher recruitment and mortality rate than sprouts, and shrubs showed higher recruitment than trees. ENSO strongly impacted both the dynamics and trajectory of succession, creating transient fluctuations in the abundance and species richness of the communities. Overall, there was a net decline in plant and species density in most successional stages along the years. Therefore, strong drought events have critical consequences for regeneration dynamics, delaying the successional process and modifying the resilience of these systems.
    Using FLUXNET data to improve models of springtime vegetation activity onset in forest ecosystems
    Melaas, E. ; Richardson, A. ; Friedl, M. ; Dragoni, D. ; Gough, C. ; Herbst, M. ; Montagnani, L. ; Moors, E.J. - \ 2013
    Agricultural and Forest Meteorology 171-172 (2013). - ISSN 0168-1923 - p. 46 - 56.
    terrestrial biosphere model - deciduous forest - co2 exchange - temperate regions - soil-temperature - phenology model - carbon-dioxide - annual cycle - bud-burst - trees
    Vegetation phenology is sensitive to climate change and variability, and is a first order control on the carbon budget of forest ecosystems. Robust representation of phenology is therefore needed to support model-based projections of how climate change will affect ecosystem function. A variety of models have been developed to predict species or site-specific phenology of trees. However, extension of these models to other sites or species has proven difficult. Using meteorological and eddy covariance data for 29 forest sites (encompassing 173 site-years), we evaluated the accuracy with which 11 different models were able to simulate, as a function of air temperature and photoperiod, spatial and temporal variability in the onset of spring photosynthetic activity. In parallel, we also evaluated the accuracy with which dynamics in remotely sensed vegetation indices from MODIS captured the timing of spring onset. To do this, we used a subset of sites in the FLUXNET La Thuile database located in evergreen needleleaf and deciduous broadleaf forests with distinct active and dormant seasons and where temperature is the primary driver of seasonality. As part of this analysis we evaluated predictions from refined versions of the 11 original models that include parameterizations for geographic variation in both thermal and photoperiod constraints on phenology. Results from cross-validation analysis show that the refined models predict the onset of spring photosynthetic activity with significantly higher accuracy than the original models. Estimates for the timing of spring onset from MODIS were highly correlated with the onset of photosynthesis derived from flux measurements, but were biased late for needleleaf sites. Our results demonstrate that simple phenology models can be used to predict the timing of spring photosynthetic onset both across sites and across years at individual sites. By extension, these models provide an improved basis for predicting how the phenology and carbon budgets of temperature-limited forest ecosystems may change in the coming decades.
    On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning
    Lasslop, G. ; Migliavacca, M. ; Bohrer, G. ; Reichstein, M. ; Bahn, M. ; Ibrom, A. ; Jacobs, C.M.J. ; Kolari, P. ; Papale, D. ; Vesala, T. ; Wohlfart, G. ; Cescatti, A. - \ 2012
    Biogeosciences 9 (2012)12. - ISSN 1726-4170 - p. 5243 - 5259.
    net ecosystem exchange - scots pine forest - water-vapor exchange - danish beech forest - soil respiration - co2 exchange - deciduous forest - global convergence - seasonal-variation - environmental controls
    Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (R-eco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input - air, surface, bole, or soil at a specific depth - should be used. This choice is a source of uncertainty and potential biases. In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.
    An evolutionary game of leaf dynamics and its consequences for canopy structure
    Hikosaka, K. ; Anten, N.P.R. - \ 2012
    Functional Ecology 26 (2012)5. - ISSN 0269-8463 - p. 1024 - 1032.
    nitrogen-use efficiency - elevated co2 - carbon gain - photosynthetic capacity - xanthium-canadense - plant-populations - individual plants - chenopodium-album - carex-acutiformis - deciduous forest
    1. Canopy photosynthesis models combined with optimization theory have been an important tool to understand environmental responses and interspecific variations in vegetation structure and functioning, but their predictions are often quantitatively incorrect. Although evolutionary game theory and the dynamic modelling of leaf turnover have been suggested useful to solve this problem, there is no model that combines these features. 2. Here, we present such a model of leaf area dynamics that incorporates game theory. 3. Leaf area index (LAI; leaf area per unit ground area) was predicted to increase with an increasing degree of interaction between genetically distinct neighbour plants in light interception. This implies that stands of clonal plants that consist of genetically identical daughter ramets have different LAI from other plants. LAI was also sensitive to the assumed vertical pattern of leaf shedding: LAI was predicted to increase with the degree to which leaves were assumed to be shed from higher positions in the canopy. Our model provides more realistic predictions of LAI than previous static optimization, dynamic optimization or static game theoretical models. 4. We suggest that both leaf dynamics and game theoretical considerations of plant competition are indispensable to scale from individual leaf traits to the structure and functioning of vegetation stands, especially in herbaceous species.
    Redefinition and global estimation of basal ecosystem respiration rate
    Jacobs, C.M.J. ; Yuan, W. - \ 2011
    Global Biogeochemical Cycles 25 (2011). - ISSN 0886-6236
    carbon-dioxide flux - soil respiration - eddy covariance - temperature sensitivity - interannual variability - co2 exchange - deciduous forest - climate-change - mediterranean forest - european forests
    Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from similar to 3 degrees S to similar to 70 degrees N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr (-1), with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.
    Diversity and production of Ethiopian dry woodlands explained by climate- and soil- stress gradients
    Eshete, A. ; Sterck, F.J. ; Bongers, F. - \ 2011
    Forest Ecology and Management 261 (2011)9. - ISSN 0378-1127 - p. 1499 - 1509.
    species-diversity - altitudinal gradients - boswellia-papyrifera - deciduous forest - african savanna - rain-forest - costa-rica - frankincense - regeneration - communities
    Dry woodlands cover about 14% of the total African land surface and represent about 25% of the natural vegetation. They are characterized by a seasonal climate, with a dry season of 4–7 months. Large parts of these ecosystems are degrading due to grazing, fire or exploitation by people. We studied species richness and productivity patterns of dry woodlands in Ethiopia. For such ecosystems, classic productivity and diversity hypotheses predict that species richness and productivity increase as the wet season length increases, and decrease when soil conditions create water stress. We inventoried and measured trees in 18 2-ha plots distributed in two sites, one higher altitude site with a shorter wet season than the lower altitude site. We found that the stand volume per hectare was lower in the site with a shorter wet season. Across all 18 plots we observed that stand volume decreased with soil water stress (estimated from texture and depth). This was in line with the prediction. The species richness was lower in the short-wet-season woodlands, but was unaffected by variation in soil conditions. This suggests that climate driven constraints (wet season length) set the limits to species richness, and not soil conditions. As far as we know, this study is one of the first studies that evaluated these productivity and diversity hypotheses for dry African woodlands. --------------------------------------------------------------------------------
    Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data
    Groenendijk, M. ; Dolman, A.J. ; Ammann, C. ; Arneth, A. ; Cescatti, A. ; Molen, M.K. van der; Moors, E.J. - \ 2011
    Journal of Geophysical Research: Biogeosciences 116 (2011). - ISSN 2169-8953 - 18 p.
    net ecosystem exchange - carbon-dioxide exchange - water-vapor exchange - sub-alpine forest - deciduous forest - co2 exchange - pine forest - terrestrial biosphere - vegetation model - ponderosa pine
    Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (a) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAIF. Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter a is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen
    Seasonal hysteresis of net ecosystem exchange in response to temperature change: Patterns and causes
    Niu, S. ; Luo, Y. ; Montagnani, L. ; Janssens, I.A. ; Gielen, B. ; Rambal, S. ; Moors, E.J. ; Matteucci, G. - \ 2011
    Global Change Biology 17 (2011)10. - ISSN 1354-1013 - p. 3102 - 3114.
    carbon-dioxide exchange - scots pine forest - sub-alpine forest - soil respiration - deciduous forest - solar-radiation - boreal forest - co2 exchange - beech forest - southern finland
    Understanding how net ecosystem exchange (NEE) changes with temperature is central to the debate on climate change-carbon cycle feedbacks, but still remains unclear. Here, we used eddy covariance measurements of NEE from 20 FLUXNET sites (203 site-years of data) in mid- and high-latitude forests to investigate the temperature response of NEE. Years were divided into two half thermal years (increasing temperature in spring and decreasing temperature in autumn) using the maximum daily mean temperature. We observed a parabolic-like pattern of NEE in response to temperature change in both the spring and autumn half thermal years. However, at similar temperatures, NEE was considerably depressed during the decreasing temperature season as compared with the increasing temperature season, inducing a counter-clockwise hysteresis pattern in the NEE–temperature relation at most sites. The magnitude of this hysteresis was attributable mostly (68%) to gross primary production (GPP) differences but little (8%) to ecosystem respiration (ER) differences between the two half thermal years. The main environmental factors contributing to the hysteresis responses of NEE and GPP were daily accumulated radiation. Soil water content (SWC) also contributed to the hysteresis response of GPP but only at some sites. Shorter day length, lower light intensity, lower SWC and reduced photosynthetic capacity may all have contributed to the depressed GPP and net carbon uptake during the decreasing temperature seasons. The resultant hysteresis loop is an important indicator of the existence of limiting factors. As such, the role of radiation, LAI and SWC should be considered when modeling the dynamics of carbon cycling in response to temperature change.
    Thermal adaptation of net ecosystem exchange
    Yuan, W. ; Luo, Y. ; Liang, S. ; YU, G. ; Niu, S. ; Stoy, J. ; Chen, J. ; Desai, A.R. ; Lindroth, A. ; Gough, C.M. ; Ceulenmans, R. ; Arain, A. ; Bernhofer, C. ; Cook, B. ; Cook, D.R. ; Dragoni, D. ; Gielen, B. ; Janssens, I.A. ; Longdoz, B. ; Liu, H. ; Lund, M. ; Matteucci, G. ; Moors, E.J. ; Scott, R.L. ; Seufert, G. ; Varner, R. - \ 2011
    Biogeosciences 8 (2011)6. - ISSN 1726-4170 - p. 1453 - 1463.
    carbon-dioxide exchange - long-term measurements - oak-dominated forest - scots pine forest - sub-alpine forest - soil respiration - deciduous forest - interannual variability - temperate forest - european forests
    Thermal adaptation of gross primary production and ecosystem respiration has been well documented over broad thermal gradients. However, no study has examined their interaction as a function of temperature, i.e. the thermal responses of net ecosystem exchange of carbon (NEE). In this study, we constructed temperature response curves of NEE against temperature using 380 site-years of eddy covariance data at 72 forest, grassland and shrubland ecosystems located at latitudes ranging from ~29° N to 64° N. The response curves were used to define two critical temperatures: transition temperature (Tb) at which ecosystem transfer from carbon source to sink and optimal temperature (To) at which carbon uptake is maximized. Tb was strongly correlated with annual mean air temperature. To was strongly correlated with mean temperature during the net carbon uptake period across the study ecosystems. Our results imply that the net ecosystem exchange of carbon adapts to the temperature across the geographical range due to intrinsic connections between vegetation primary production and ecosystem respiration.
    Controls on winter ecosystem respiration in temperate and boreal ecosystems
    Ciais, P. ; Wang, T. ; Piao, S.L. ; Ottlé, C. ; Brender, P. ; Moors, E.J. - \ 2011
    Biogeosciences 8 (2011)7. - ISSN 1726-4170 - p. 2009 - 2025.
    carbon-dioxide exchange - atmosphere co2 exchange - sub-alpine forest - net ecosystem - soil respiration - interannual variability - deciduous forest - northern wisconsin - vegetation types - hardwood forest
    Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal patterns of winter ecosystem respiration (Reco) of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data from 57 ecosystem sites ranging from ~35° N to ~70° N. Deciduous forests were characterized by the highest winter Reco rates (0.90 ± 0.39 g C m-2 d-1), when winter is defined as the period during which daily air temperature remains below 0 °C. By contrast, arctic wetlands had the lowest winter Reco rates (0.02 ± 0.02 g C m-2 d-1). Mixed forests, evergreen needle-leaved forests, grasslands, croplands and boreal wetlands were characterized by intermediate winter Reco rates (g C m-2 d-1) of 0.70(±0.33), 0.60(±0.38), 0.62(±0.43), 0.49(±0.22) and 0.27(±0.08), respectively. Our cross site analysis showed that winter air (Tair) and soil (Tsoil) temperature played a dominating role in determining the spatial patterns of winter Reco in both forest and managed ecosystems (grasslands and croplands). Besides temperature, the seasonal amplitude of the leaf area index (LAI), inferred from satellite observation, or growing season gross primary productivity, which we use here as a proxy for the amount of recent carbon available for Reco in the subsequent winter, played a marginal role in winter CO2 emissions from forest ecosystems. We found that winter Reco sensitivity to temperature variation across space (QS) was higher than the one over time (interannual, QT). This can be expected because QS not only accounts for climate gradients across sites but also for (positively correlated) the spatial variability of substrate quantity. Thus, if the models estimate future warming impacts on Reco based on QS rather than QT, this could overestimate the impact of temperature changes
    On the segregation of chemical species in a clear boundary layer over heterogeneous land surfaces
    Ouwersloot, H.G. ; Vilà-Guerau de Arellano, J. ; Heerwaarden, C.C. van; Ganzeveld, L.N. ; Krol, M.C. ; Lelieveld, J. - \ 2011
    Atmospheric Chemistry and Physics 11 (2011). - ISSN 1680-7316 - p. 10681 - 10704.
    large-eddy simulation - volatile organic-compounds - tropical rain-forest - atmospheric chemistry - deciduous forest - heat-flux - emission - campaign - scale - turbulence
    Using a Large-Eddy Simulation model, we have systematically studied the inability of boundary layer turbulence to efficiently mix reactive species. This creates regions where the species are accumulated in a correlated or anti-correlated way, thereby modifying the mean reactivity. We quantify this modification by the intensity of segregation, IS, and analyse the driving mechanisms: heterogeneity of the surface moisture and heat fluxes, various background wind patterns and non-uniform isoprene emissions. The heterogeneous surface conditions are characterized by cool and wet forested patches with high isoprene emissions, alternated with warm and dry patches that represents pasture with relatively low isoprene emissions. For typical conditions in the Amazon rain forest, applying homogeneous surface forcings and in the absence of free tropospheric NOx, the isoprene- OH reaction rate is altered by less than 10 %. This is substantially smaller than the previously assumed IS of 50% in recent large-scale model analyses of tropical rain forest chemistry. Spatial heterogeneous surface emissions enhance the segregation of species, leading to alterations of the chemical reaction rates up to 20 %. The intensities of segregation are enhanced when the background wind direction is parallel to the borders between the patches and reduced in the case of a perpendicular wind direction. The effects of segregation on trace gas concentrations vary per species. For the highly reactive OH, the differences in concentration averaged over the boundary layer are less than 2% compared to homogeneous surface conditions, while the isoprene concentration is increased by as much as 12% due to the reduced chemical reaction rates. These processes take place at the sub-grid scale of chemistry transport models and therefore need to be parameterized.
    Environmental changes during secondary succession in a tropical dry forest in Mexico
    Lebrija Trejos, E.E. ; Pérez-Garcia, E.A. ; Meave, J. ; Poorter, L. ; Bongers, F. - \ 2011
    Journal of Tropical Ecology 27 (2011)05. - ISSN 0266-4674 - p. 477 - 489.
    vapor-pressure deficit - rain-forest - plant-communities - deciduous forest - tree seedlings - gas-exchange - costa-rica - microclimate - canopy - light
    Vegetation and environment change mutually during secondary succession, yet the idiosyncrasies of the vegetation effect on the understorey environment are poorly understood. To test whether the successional understorey environment changes predictably and is shaped by the structure and seasonality of tropical dry forests, we estimated basal area and vegetation cover, and measured understorey temperature, light and moisture conditions, in 17 plots forming a 60-y chronosequence and a mature forest. Light and air and soil temperature decreased with time (75-15% of open-sky radiation, 31.7-29.3 °C, and +2.5 °C to -0.5 °C relative to ambient, respectively), whereas relative humidity increased (67-74%). Soil water availability increased with early-successional development (-45 to -1 kPa) but decreased afterwards (to -18 kPa). The first axis of a PCA of the rainy-season environment explained 60% of the variation and was strongly related to air temperature and relative humidity. During tropical dry-forest succession, such factors may be more important than light, the reduction in which is not extreme compared with taller and more vertically stratified wet forests. Seasonality significantly affected the successional environmental gradients, which were marked mainly during the wet season. Environmental heterogeneity was higher in the wet than in the dry season, and larger for resources (light and water) than for conditions (temperature and humidity). The wet-season increase in environmental heterogeneity potentially creates differential growing scenarios; the environmental harshness of the dry season would mostly challenge seedling survival.
    Analysis of monotonic greening and browning trends from global NDVI time-series
    Jong, R. de; Bruin, S. de; Wit, A.J.W. de; Schaepman, M.E. ; Dent, D.L. - \ 2011
    Remote Sensing of Environment 115 (2011)2. - ISSN 0034-4257 - p. 692 - 702.
    avhrr vegetation index - land degradation - spot-vegetation - growing-season - photosynthetic trends - primary productivity - deciduous forest - plant phenology - carbon-dioxide - high-latitudes
    Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.
    Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites
    Migliavacca, M. ; Reichstein, M. ; Richardson, A.D. ; Colombo, R. ; Sutton, M.A. ; Lasslop, G. ; Tomelleri, E. ; Wohlfahrt, G. ; Carvalhais, N. ; Molen, M.K. van der - \ 2011
    Global Change Biology 17 (2011)1. - ISSN 1354-1013 - p. 390 - 409.
    forest soil respiration - carbon-dioxide exchange - water-vapor exchange - deciduous forest - european forests - heterotrophic components - rhizosphere respiration - terrestrial ecosystems - litter decomposition - nitrogen deposition
    In this study we examined ecosystem respiration (RECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of RECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of RECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of RECO. The maximum seasonal leaf area index (LAIMAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature Tref515 1C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r250.52, Po0.001, n5104) even within each PFT. Besides LAIMAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (Ndepo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAIMAX) which performed well in predicting the spatio-temporal variability of RECO, explaining 470% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands
    Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data
    Groenendijk, M. ; Dolman, A.J. ; Molen, M.K. van der; Leuning, R. ; Arneth, A. ; Delpierre, N. ; Gash, J.H.C. ; Lindroth, A. ; Richardson, A.D. ; Verbeeck, H. ; Wohlfahrt, G. - \ 2011
    Agricultural and Forest Meteorology 151 (2011)1. - ISSN 0168-1923 - p. 22 - 38.
    net ecosystem exchange - carbon-dioxide exchange - atmosphere-biosphere system - biochemically based model - tower-based measurements - water-vapor exchange - deciduous forest - co2 exchange - pine forest - interannual variability
    The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes
    Check title to add to marked list
    << previous | next >>

    Show 20 50 100 records per page

    Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.