Small-Scale Forest Structure Influences Spatial Variability of Belowground Carbon Fluxes in a Mature Mediterranean Beech Forest

The tree belowground compartment, especially fine roots, plays a relevant role in the forest ecosystem carbon (C) cycle, contributing largely to soil CO2 efflux (SR) and to net primary production (NPP). Beyond the well-known role of environmental drivers on fine root production (FRP) and SR, other determinants such as forest structure are still poorly understood. We investigated spatial variability of FRP, SR, forest structural traits, and their reciprocal interactions in a mature beech forest in the Mediterranean mountains. In the year of study, FRP resulted in the main component of NPP and explained about 70% of spatial variability of SR. Moreover, FRP was strictly driven by leaf area index (LAI) and soil water content (SWC). These results suggest a framework of close interactions between structural and functional forest features at the local scale to optimize C source–sink relationships under climate variability in a Mediterranean mature beech forest.

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Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Ecosystems ◽

10.1007/s10021-020-00481-z ◽

2020 ◽

Vol 23 (7) ◽

pp. 1464-1480 ◽

Cited By ~ 2

Author(s):

Jake D. Graham ◽

Nancy F. Glenn ◽

Lucas P. Spaete ◽

Paul J. Hanson

Keyword(s):

Spatial Variability ◽

Quantitative Methods ◽

Spatial Scales ◽

Methane Flux ◽

Small Scale ◽

Classification Methods ◽

Ecological Processes ◽

Elevation Gradients ◽

C Cycle ◽

Gradient Based

AbstractPeatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

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Robust processing of airborne laser scans to plant area density profiles

Biogeosciences ◽

10.5194/bg-17-5939-2020 ◽

2020 ◽

Vol 17 (23) ◽

pp. 5939-5952

Author(s):

Johan Arnqvist ◽

Julia Freier ◽

Ebba Dellwik

Keyword(s):

Beech Forest ◽

Airborne Lidar ◽

Small Scale ◽

Average Intensity ◽

Forest Site ◽

Area Index ◽

Area Density ◽

Intensity Information ◽

Plant Area Index ◽

Plant Area

Abstract. We present a new algorithm for the estimation of the plant area density (PAD) profiles and plant area index (PAI) for forested areas based on data from airborne lidar. The new element in the algorithm is to scale and average returned lidar intensities for each lidar pulse, whereas other methods do not use the intensity information at all, use only average intensity values, or do not scale the intensity information, which can cause problems for heterogeneous vegetation. We compare the performance of the new algorithm to three previously published algorithms over two contrasting types of forest: a boreal coniferous forest with a relatively open structure and a dense beech forest. For the beech forest site, both summer (full-leaf) and winter (bare-tree) scans are analyzed, thereby testing the algorithm over a wide spectrum of PAIs. Whereas all tested algorithms give qualitatively similar results, absolute differences are large (up to 400 % for the average PAI at one site). A comparison with ground-based estimates shows that the new algorithm performs well for the tested sites. Specific weak points regarding the estimation of the PAD from airborne lidar data are addressed including the influence of ground reflections and the effect of small-scale heterogeneity, and we show how the effect of these points is reduced in the new algorithm, by combining benefits of earlier algorithms. We further show that low-resolution gridding of the PAD will lead to a negative bias in the resulting estimate according to Jensen's inequality for convex functions and that the severity of this bias is method dependent. As a result, the PAI magnitude as well as heterogeneity scales should be carefully considered when setting the resolution for the PAD gridding of airborne lidar scans.

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Moderate forest disturbance as a stringent test for gap and big-leaf models

Biogeosciences ◽

10.5194/bg-12-513-2015 ◽

2015 ◽

Vol 12 (2) ◽

pp. 513-526 ◽

Cited By ~ 11

Author(s):

B. Bond-Lamberty ◽

J. P. Fisk ◽

J. A. Holm ◽

V. Bailey ◽

G. Bohrer ◽

...

Keyword(s):

Primary Production ◽

Tree Mortality ◽

Net Primary Production ◽

Forest Disturbance ◽

Gross Primary Production ◽

Structural Complexity ◽

Terrestrial Ecosystem ◽

Ecosystem Models ◽

Area Index ◽

C Cycle

Abstract. Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

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A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield

Geoscientific Model Development ◽

10.5194/gmd-8-3785-2015 ◽

2015 ◽

Vol 8 (11) ◽

pp. 3785-3800 ◽

Cited By ~ 18

Author(s):

Y. Fan ◽

O. Roupsard ◽

M. Bernoux ◽

G. Le Maire ◽

O. Panferov ◽

...

Keyword(s):

Oil Palm ◽

Net Primary Production ◽

Leaf Growth ◽

Canopy Structure ◽

Field Measurements ◽

Fruit Yield ◽

Small Scale ◽

Area Index ◽

Community Land Model ◽

Site Variability

Abstract. In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

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Spatial variability of soil CO2 efflux linked to soil parameters and ecosystem characteristics in a temperate beech forest

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2011.11.003 ◽

2012 ◽

Vol 154-155 ◽

pp. 136-146 ◽

Cited By ~ 47

Author(s):

Jérôme Ngao ◽

Daniel Epron ◽

Nicolas Delpierre ◽

Nathalie Bréda ◽

André Granier ◽

...

Keyword(s):

Spatial Variability ◽

Beech Forest ◽

Soil Co2 Efflux ◽

Soil Parameters ◽

Co2 Efflux ◽

Soil Co2

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Small Scale Rainfall Partitioning in a European Beech Forest Ecosystem Reveals Heterogeneity of Leaf Area Index and Its Connectivity to Hydro-and Atmosphere

Geosciences ◽

10.3390/geosciences9090393 ◽

2019 ◽

Vol 9 (9) ◽

pp. 393 ◽

Cited By ~ 3

Author(s):

Nico Frischbier ◽

Katharina Tiebel ◽

Alexander Tischer ◽

Sven Wagner

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Forest Ecosystem ◽

Spatial Scales ◽

European Beech ◽

Beech Forest ◽

Small Scale ◽

Litter Production ◽

Area Index ◽

Average Value

(1) Background: Leaf area index (LAI) is an essential structural property of plant canopies and is functionally related to fluxes of energy, water, carbon, and light in ecosystems; coupling the biosphere to the geo-, hydro-, and atmosphere. There is an increasing need for more accurate and traceable measurements among several spatial scales of investigation and modelling. We hypothesize that the spatial variability of LAI at the scale of crown sections of a single European beech (Fagus sylvatica L.) tree in a highly structured, mixed European beech-Norway spruce stand can be determined by simultaneous records of precipitation; (2) Methods: Spatially explicit measurements of throughfall were conducted repeatedly below beech and in forest gaps for rain events in leafed and in leafless periods. Subsequent analysis with a new regression approach resulted in estimating leaf and twig water storage capacities (SCleaf/twig) at point level independent of within-crown lateral flow mechanisms. Inverse modelling was used to estimate spatial litterfall (n = 99) distribution and litter production (mass, area, numbers) for single trees, as a function of diameter at breast height; (3) Results: As revealed by a linear mixed-effects model, SCleaf at the center of a beech canopies amounts to 4.9 mm in average and significantly decreases in the direction of the crown edges to an average value of 1.1 mm. Based on diameter-sensitive prediction of litter production, specific leaf area wetting capacity amounts to 0.260 l·m−2. A linear within-canopy dynamic of LAI was found with a mean of 17.6 m2·m−2 in the center and 4.0 m2·m−2 at the edges; and (4) Conclusions: The application of the method provided plausible results and can be extended to further throughfall datasets and tree species. Unravelling the causes and magnitude of spatial- and temporal heterogeneity of forest ecosystem properties contribute to overall progress in geosciences by improving the understanding how the biosphere relates to the hydro- and atmosphere.

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Moderate forest disturbance as a stringent test for gap and big-leaf models

Biogeosciences Discussions ◽

10.5194/bgd-11-11217-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 11217-11248 ◽

Cited By ~ 2

Author(s):

B. Bond-Lamberty ◽

J. Fisk ◽

J. A. Holm ◽

V. Bailey ◽

C. M. Gough

Keyword(s):

Tree Mortality ◽

Net Primary Production ◽

Forest Disturbance ◽

Structural Complexity ◽

Terrestrial Ecosystem ◽

Ecosystem Models ◽

Area Index ◽

C Cycle ◽

Key Factor ◽

Big Leaf Model

Abstract. Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

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Robust processing of airborne laser scans to plant area density profiles

10.5194/bg-2020-121 ◽

2020 ◽

Author(s):

Johan Arnqvist ◽

Julia Freier ◽

Ebba Dellwik

Keyword(s):

Beech Forest ◽

Airborne Lidar ◽

Small Scale ◽

Average Intensity ◽

Forest Site ◽

Area Index ◽

Area Density ◽

Intensity Information ◽

Plant Area Index ◽

Plant Area

Abstract. We present a new algorithm for the estimation of plant area density (PAD) proﬁles and plant area index (PAI) for forested areas based on data from airborne lidar. The new element in the algorithm is to scale and average returned lidar intensities for each lidar pulse, whereas other methods either do not use the intensity information at all, only use average intensity values or do not scale the intensity information, which can cause problems for heterogeneous vegetation. We compare the performance of the new and three previously published algorithms over two contrasting types of forest: a boreal coniferous forest with a relatively open structure and a dense beech forest. For the beech forest site, both summer (full leaf) and winter (bare trees) scans are analyzed, thereby testing the algorithm over a wide spectrum of PAIs. Whereas all tested algorithms give qualitatively similar results, absolute differences are large (up to 400 % for the average PAI at one site). A comparison with ground-based estimates shows that the new algorithm performs well for the tested sites, and further and more importantly – it never produces clearly dubious results. Speciﬁc weak points for estimation of PAD from airborne lidar data are addressed; the inﬂuence of ground reﬂections and the effect of small-scale heterogeneity, and we show how the effect of these points is minimized using the new algorithm. We further show that low-resolution gridding of PAD will lead to a negative bias in the resulting estimate according to Jensen’s inequality for concave functions, and that the severity of this bias is method-dependent. As a result, PAI magnitude as well as heterogeneity scales should be carefully considered when setting the resolution for PAD gridding of airborne lidar scans.

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