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Estimation of leaf area index with the Li-Cor LAI 2000 in deciduous forests
Abstract
The present study has been performed in Italy, in stands of the main broad-leaved forest species. Thinned and unthinned stands of Quercus cerris L. (6.3% of total area covered by deciduous species in Italy), Castanea sativa L., (8.5%) and Fagus sylvatica L. (12.6%) were selected from 15 permanent plots. LAI data have been collected during the 3 years (1993–1995), using both direct (littertraps) and indirect methods (LAI-2000 Plant Canopy Analyzer, PCA, Li-Cor, Lincoln, NE, USA). LAI estimation by litter collection (LAILT, 3.2–7.6 m2 m−2) was in the range of values reported for deciduous forest, while the PCA method generally underestimated the LAI (LAIPCA, 1.8–5.8 m2 m−2). Average underestimation was 26.5%, being similar to other reports. The underestimation was higher in thinned (29.1%±14.7%) than in unthinned (22.2%±12.2%) stands and in stands characterised by a LAILT>5 m2 m−2. On the contrary, in stands with LAILT<5 m2 m−2, PCA estimates were closer to littertraps ones (−11%±9.6%). On the average, LAILT was 4.51±0.92 m2 m−2 and 5.86±0.11 m2 m−2, for thinned and unthinned stands, respectively. Also PCA was able to estimate this difference, arriving at 3.14±0.70 m2 m−2 (thinned stands) and 4.47±0.61 m2 m−2 (unthinned stands). With both methods, the difference between the two stand types was strongly significant. Although LAIPCA values were always below LAILT, the correlation between the two data sets was linear and significant. When recalculated omitting the reading of the external PCA ring, the correlation between LAILT and LAIPCA improved, and the underestimation of LAIPCA was within 12%. Woody area index (WAI) was evaluated with the PCA during the leafless period. The instrument was able to show the difference between thinned (0.55±0.09) and unthinned stands (0.80±0.19). Similar to other studies, the subtraction of WAI from LAIPCA values increased the underestimation of LAILT. The agreement between the two methods for LAI estimation was satisfactory. Nevertheless, the underestimation by the PCA method must be taken into account. Over different years and stands, the variability of underestimation was not marked, pointing to a reliable use of PCA in different conditions, as, for example, the comparison of thinned and unthinned stands and in measuring temporal and spatial variations of LAI. The overlapping of leaves, the presence of gaps within the canopy and light at the horizon level seem to be some of the important variables that influence LAI estimation by the PCA. Further corrections of the data can improve substantially the performance of the PCA and produce reliable LAI estimates even though the collection of direct reference measurements is strongly recommended to know exactly LAI, in order to assess instrument performance in a given site.
... Field LAI measurements can be categorized into direct and indirect methods. Direct measurements methods include destructive sampling (Chen, 1996;Gower et al., 1999;Smith et al., 1993), leaf litter collection (Breda, 2003;Cutini et al., 1998;Liu et al., 2015), and point contact sampling (Cutini et al., 1998). These typically serve as accurate references to validate parameters interpreted by indirect methods. ...
... Field LAI measurements can be categorized into direct and indirect methods. Direct measurements methods include destructive sampling (Chen, 1996;Gower et al., 1999;Smith et al., 1993), leaf litter collection (Breda, 2003;Cutini et al., 1998;Liu et al., 2015), and point contact sampling (Cutini et al., 1998). These typically serve as accurate references to validate parameters interpreted by indirect methods. ...
... For crops, the performance of indirect measurements was comparable with that of the labor-intensive direct methods (Baret et al., 2010;Demarez et al., 2008;Fang et al., 2018bFang et al., , 2014Stroppiana et al., 2006). For continuous forests, the influences of leaf clumping and woody organs must be addressed when applying indirect methods (Chen et al., 2006(Chen et al., , 1997Chen and Cihlar, 1995;Chianucci and Cutini, 2013;Cutini et al., 1998;Leblanc and Chen, 2001;Leblanc and Fournier, 2014;Ryu et al., 2012Ryu et al., , 2010. Indirect field measurements are currently used to calibrate and validate remote sensing products for continuous vegetation (Abuelgasim et al., 2006;Baret et al., 2013;Chen et al., 2002;Claverie et al., 2013;Degerickx et al., 2018;Fang et al., 2012;Hancock et al., 2017;Ma et al., 2014;Moeser et al., 2014;Solberg et al., 2006). ...
Field measurements of leaf area density (LAD) and leaf area index (LAI) for individual trees have increased in importance and relevance with the advent of high spatial resolution remote sensing for the urban landscape. However, indirect field measurements of LAD/LAI for widely dispersed individual trees have not been comprehensively evaluated. The present study compares the accuracy of three indirect LAD/LAI estimation methods, including single-return terrestrial laser scanning (TLS), LAI-2200, and digital hemispherical photography (DHP) on urban trees. To this end, field measurements were inter-compared and physically modeled by discrete anisotropic radiation transfer (DART). The inter-comparisons of field data revealed substantial inconsistencies between DHP and the other two approaches. For the physical modeling, reference LAI was obtained from realistic 3-D tree objects in DART, and the LAD/LAI was derived from simulated TLS, LAI-2200, and DHP acquisitions and was evaluated against the references. The physical modeling results showed that TLS could reasonably estimate LAD/LAI for LAD < 3 and LAI < 6 using a small (0.3 m) voxel size. However, the measurements became saturated for dense foliage (LAD > 3 and LAI > 6). The LAD/LAI accuracy was sharply reduced as voxel size increased. In addition, the trunks caused overestimation for both of LAD and LAI, while branches caused LAD underestimation and LAI overestimation. Further research is needed to compensate for the effects of occlusions and clumping in the estimates of LAD/LAI for dense-foliated trees using TLS. LAI-2200 grossly underestimated LAD for all cases, while it accurately estimated LAI for LAI < 5 and became gradually saturated for LAI > 5. The estimation accuracy of LAI-2200 declined markedly with increasing uncertainty in crown shape. The 90° view cap had higher accuracy than the 180° or 270° view caps using four or all five LAI-2200 rings. Additional sensors or algorithms for crown shape measurement should be developed for LAI-2200 to reduce its reliance on other data sources. DHP is not recommended for individual trees as the LAI estimations were biased from the reference values, and improvements in reliability will depend on new algorithms to account for differences in path length. These results serve as a benchmark for evaluating the accuracy of in situ LAD/LAI measurement techniques and for optimizing the configurations required for each indirect measurement method applied to individual trees.
... Ω e (θ) is the Ω e at θ derived from the gap size distribution (CC), logarithmic averaging (LX), and combination of gap size and logarithmic averaging (CLX) using Equations (1)-(3), respectively. p e (57) and Ω e (57) are the canopy element gap fraction and Ω e measurements obtained at the zenith angle range of 52 • -62 • , respectively. θ i , p e_i (θ i ), Ω e_i , and W i are the center zenith angle, canopy element gap fraction, Ω e and weight factor of the i th annulus of digital hemispherical photography (DHP) or multispectral canopy imager (MCI), respectively. ...
... The seventh annulus (55 • -65 • ) of MCI was adopted by the Beer inversion model in the LAI estimation. One group of six PAI estimates (one estimate for each combination of the Ω e algorithm and the inversion model) was calculated using Equations (8) and (11) based on the p e_i (θ i ), p e (57), Ω e_i , and Ω e (57), which were calculated from the classified leaf-on MCI images, and corrected needle-to-shoot area ratio measurements. Two groups of twelve WAI estimates (one estimate for each combination of the Ω w algorithm and inversion model) were derived using Equations (8) and (11) based on the p w_i (θ i ), p w (57), Ω w_i , and Ω w (57) measurements that were calculated from the classified leaf-on and leaf-off MCI images, respectively. ...
... One group of six PAI estimates (one estimate for each combination of the Ω e algorithm and the inversion model) was calculated using Equations (8) and (11) based on the p e_i (θ i ), p e (57), Ω e_i , and Ω e (57), which were calculated from the classified leaf-on MCI images, and corrected needle-to-shoot area ratio measurements. Two groups of twelve WAI estimates (one estimate for each combination of the Ω w algorithm and inversion model) were derived using Equations (8) and (11) based on the p w_i (θ i ), p w (57), Ω w_i , and Ω w (57) measurements that were calculated from the classified leaf-on and leaf-off MCI images, respectively. Then, 12 LAI estimates were derived from the MCI in each forest using Equation (16) based on the one PAI group and two WAI group measurements. ...
Optical methods are frequently used as a routine method to obtain the elementary sampling unit (ESU) leaf area index (LAI) of forests. However, few studies have attempted to evaluate whether the ESU LAI obtained from optical methods matches the accuracy required by the LAI map product validation community. In this study, four commonly used optical methods, including digital hemispherical photography (DHP), digital cover photography (DCP), tracing radiation of canopy and architecture (TRAC) and multispectral canopy imager (MCI), were adopted to estimate the ESU (25 m × 25 m) LAI of five Larix principis-rupprechtii forests with contrasting structural characteristics. The impacts of three factors, namely, inversion model, canopy element or woody components clumping index (Ωe or Ωw) algorithm, and the woody components correction method, on the ESU LAI estimation of the four optical methods were analyzed. Then, the LAI derived from the four optical methods was evaluated using the LAI obtained from litter collection measurements. Results show that the performance of the four optical methods in estimating the ESU LAI of the five forests was largely affected by the three factors. The accuracy of the LAI obtained from the DHP and MCI strongly relied on the inversion model, the Ωe or Ωw algorithm, and the woody components correction method adopted in the estimation. Then the best Ωe or Ωw algorithm, inversion model and woody components correction method to be used to obtain the ESU LAI of L. principis-rupprechtii forests with the smallest root mean square error (RMSE) and mean absolute error (MAE) were identified. Amongst the three typical woody components correction methods evaluated in this study, the woody-to-total area ratio obtained from the destructive measurements is the most effective method for DHP to derive the ESU LAI with the smallest RMSE and MAE. In contrast, using the woody area index obtained from the leaf-off DHP or DCP images as the woody components correction method would result in a large LAI underestimation. TRAC and MCI outperformed DHP and DCP in the ESU LAI estimation of the five forests, with the smallest RMSE and MAE. All the optical methods, except DCP, are qualified to obtain the ESU LAI of L. principis-rupprechtii forests with an MAE of <20% that is required by the global climate observation system. None of the optical methods, except TRAC, show the potential to obtain the ESU LAI of L. principis-rupprechtii forests with an MAE of <5%.
... Therefore, most researchers intended to simplify the sampling protocols for measuring SLA. For instance, some studies applied the SLA sampled from one trap (e.g., Cutini et al., 1998), while others used an average SLA from one plot or all plots (Liu et al., 2015a), i.e., neglected intra-or inter-plot variation. However, Bouriaud et al. (2003) found that neglecting the inter-plot variation in SLA overestimated the LAI by 8 -24% in a beech stand. ...
... The 10 simplified SLA sampling protocols produced biases in LAI estimates ranging between − 12.4% and 22.2% relative to the reference protocol (Table A6). Such a magnitude is significant compared with the difference between optical and the litterfall methods [12% by Cutini et al. (1998) and 7% at this site (Liu et al., 2015c)], and the errors in MODIS LAI [34% in the Harvard forest (Pisek and Chen, 2007) and 9% without the herbaceous LAI in this study]. ...
Litterfall collection is a non-destructive direct method to estimate forest leaf area index (LAI) and validate indirect LAI products. However, the potential errors associated with the variation in specific leaf area (SLA) are rarely explored. Here, we measured the SLA of leaf litter for each tree species in a temperate deciduous forest using the litterfall collection method from 2012 to 2018, and assessed the spatial and temporal variation in SLA and its consequence on LAI estimates. The results showed that the spatial and temporal variation in SLA for the 10 major species across the seven years ranged from 0.8% to 24.3%, with the variation across the nine permanent plots (20 m × 30 m) being higher than that within plot (five 1-m² traps), and interannual higher than seasonal. Across the 63 plot-years, the 10 simplified SLA sampling protocols introduced the errors in LAI by −12.4% to 22.2% relative to the reference protocol (sampling leaves from each trap at each collection date for the major species). Applying the SLA obtained from one trap in each plot, one plot, at the leaf fall peak for each year, or for a single year induced the errors in LAI by –3.7% to 2.9%, −6.4% to 14.7%, −9.2% to 4.7%, and −8.1% to 8.6%, respectively. Considering the trade-off between inter-plot and interannual variation, we recommend sampling from one-trap for each plot at the leaf-fall peak for measuring SLA and quantifying the spatial pattern of LAI, and sampling each species in the typical plot for measuring SLA and monitoring the temporal fluctuation in LAI. The tight relationship between the MODIS and ground reference LAI across the seven years (R² = 0.77) validated the use of MODIS LAI to study the long-term change in forest LAI. These findings help to establish a standardized protocol for long-term accurately measuring forest LAI with the litterfall collection.
... RH min = daily minimum relative humidity (%) * U z = daily wind speed at 2 m above the ground (m/s) * r i = ratio between monthly average daily bright sunshine duration n(h) and monthly average maximum daily sunshine duration N(h) The leaf area index (LAI), required for the calculation of ET 0 with Penman-Monteith Equation (3), has been assumed equal to 4 m 2 /m 2 between May and August when foliage and dense underbrush are present (as indicated by [76,77] for Italian Castanea Sativa), while it has been considered negligible from November to February, when the trees are leafless. Smaller values have been assumed when foliage and underbrush are not fully developed, namely 1.5 m 2 /m 2 in March and October, and 3 m 2 /m 2 in April and September. ...
... underbrush are present (as indicated by [76,77] for Italian Castanea Sativa), while it has been considered negligible from November to February, when the trees are leafless. Smaller values have been assumed when foliage and underbrush are not fully developed, namely 1.5 / in March and October, and 3 / in April and September. ...
Many mountainous areas in Campania, Southern Italy, are characterized by steep slopes covered by loose unsaturated pyroclastic deposits laying upon fractured limestone bedrock. The soil covers are mainly constituted by layers of ashes and pumices. Large and intense rainfall events trigger shallow landslides, often turning into debris flows that cause huge damage and casualties. The slope of Cervinara, around 40 km Northeast of Naples, was involved in a catastrophic flowslide on 16 December 1999, triggered by a rainstorm of 325 mm in 48 h. To capture the main effects of precipitation on the slope stability, hydro-meteorological monitoring activities have been carried out at the slope to assess the water balance for three years (2017-2020). The field monitoring data allowed the identification of the complex hydrological processes involving the unsaturated pyroclastic soil and the shallow groundwater system developing in the limestone bedrock, which control the conditions that potentially predispose the slope to landslide triggering. Specifically, late autumn has been identified as the potentially most critical period, when slope drainage processes are not yet effective, and soil covers already receive large amounts of precipitation.
... However, at a regional scale, LAI variation can be impacted by environmental factors such as natural disturbances, site fertility, phenology, management practices, and interactions among all of these factors [10]. LAI field measurement methods have been investigated in depth through both direct and indirect methods (e.g., [11][12][13][14][15][16]). Direct methods involve estimating LAI from the destructive sampling of leaves by harvesting trees or through the use of litter traps [14][15][16]. ...
... However, at a regional scale, LAI variation can be impacted by environmental factors such as natural disturbances, site fertility, phenology, management practices, and interactions among all of these factors [10]. LAI field measurement methods have been investigated in depth through both direct and indirect methods (e.g., [11][12][13][14][15][16]). Direct methods involve estimating LAI from the destructive sampling of leaves by harvesting trees or through the use of litter traps [14][15][16]. The indirect methods can be divided into two different categories: allometric equations and optical methods. ...
Forest management treatments often translate into changes in forest structure. Understanding and assessing how forests react to these changes is key for forest managers to develop and follow sustainable practices. A strategy to remotely monitor the development of the canopy after thinning using satellite imagery time-series data is presented. The aim was to identify optimal remote sensing Vegetation Indices (VIs) to use as time-sensitive indicators of the early response of vegetation after the thinning of sweet chestnut (Castanea Sativa Mill.) coppice. For this, the changes produced at the canopy level by different thinning treatments and their evolution over time (2014–2019) were extracted from VI values corresponding to two trials involving 33 circular plots (r = 10 m). Plots were subjected to one
of the following forest management treatments: Control with no intervention (2800–3300 stems ha−1 ), Treatment 1, one thinning leaving a living stock density of 900–600 stems ha−1 and Treatment 2, a more intensive thinning, leaving 400 stems ha−1 . Time series data from Landsat-8 and Sentinel-2 were collected to calculate values for different VIs. Canopy development was computed by comparing
the area under curves (AUCs) of different VI time-series annually throughout the study period. Soil-Line VIs were compared to the Normalized Vegetation Index (NDVI) revealing that the Second
Modified Chlorophyll Absorption Ratio Index (MCARI2) more clearly demonstrated canopy evolution tendencies over time than the NDVI. MCARI2 data from both L8 and S2 reflected how the influence
of treatment on the canopy cover decreases over the years, providing significant differences in the thinning year and the year after. Metrics derived from the MCARI2 time-series also demonstrated the capacity of the canopy to recovery to pretreatment coverage levels. The AUC method generates a specific V-shaped time-signature, the vertex of which coincides with the thinning event and, as such, provides forest managers with another tool to assist decision making in the development of sustainable forest management strategies.
... Sampling schemes with various numbers and spatial arrangements of sample points have been adopted by optical methods such as DHP and LAI-2000/LAI-2200, to estimate the ESU effective plant area index (PAI e ), effective woody area index and LAI of forest plots. For example, sample points were spatially arranged in certain patterns such as circle Woodgate 2015), square (Neumann et al. 1989; Baret et al. 2005;Macfarlane et al. 2007;Ryu et al. 2010a;Pisek et al. 2011;Woodgate et al. 2012;, transect (Cutini et al. 1998;van Gardingen et al. 1999;Hyer and Goetz 2004;Abuelgasim et al. 2006;Ryu et al. 2010a;Majasalmi et al. 2012), cross (Leblanc 2008;Woodgate et al. 2012;Leblanc and Fournier 2014;Zou et al. 2018a) and dispersed (Abuelgasim et al. 2006;Majasalmi et al. 2012). Moreover, different sample sizes ranging from 1 to 176 have been applied at the ESU scale (Cutini et al. 1998;van Gardingen et al. 1999;Nackaerts et al. 2000;Macfarlane et al. 2007;Gonsamo et al. 2010;Ryu et al. 2010a;Pisek et al. 2011;Woodgate 2015;Calders et al. 2018;Zou et al. 2018a;Zou et al. 2018b). ...
... For example, sample points were spatially arranged in certain patterns such as circle Woodgate 2015), square (Neumann et al. 1989; Baret et al. 2005;Macfarlane et al. 2007;Ryu et al. 2010a;Pisek et al. 2011;Woodgate et al. 2012;, transect (Cutini et al. 1998;van Gardingen et al. 1999;Hyer and Goetz 2004;Abuelgasim et al. 2006;Ryu et al. 2010a;Majasalmi et al. 2012), cross (Leblanc 2008;Woodgate et al. 2012;Leblanc and Fournier 2014;Zou et al. 2018a) and dispersed (Abuelgasim et al. 2006;Majasalmi et al. 2012). Moreover, different sample sizes ranging from 1 to 176 have been applied at the ESU scale (Cutini et al. 1998;van Gardingen et al. 1999;Nackaerts et al. 2000;Macfarlane et al. 2007;Gonsamo et al. 2010;Ryu et al. 2010a;Pisek et al. 2011;Woodgate 2015;Calders et al. 2018;Zou et al. 2018a;Zou et al. 2018b). ...
Background
Digital hemispherical photography (DHP) is widely used to estimate the leaf area index (LAI) of forest plots due to its advantages of high efficiency and low cost. A crucial step in the LAI estimation of forest plots via DHP is choosing a sampling scheme. However, various sampling schemes involving DHP have been used for the LAI estimation of forest plots. To date, the impact of sampling schemes on LAI estimation from DHP has not been comprehensively investigated.
Methods
In this study, 13 commonly used sampling schemes which belong to five sampling types (i.e. dispersed, square, cross, transect and circle) were adopted in the LAI estimation of five Larix principis-rupprechtii plots (25 m × 25 m). An additional sampling scheme (with a sample size of 89) was generated on the basis of all the sample points of the 13 sampling schemes. Three typical inversion models and four canopy element clumping index ( Ω e ) algorithms were involved in the LAI estimation. The impacts of the sampling schemes on four variables, including gap fraction, Ω e , effective plant area index (PAI e ) and LAI estimation from DHP were analysed. The LAI estimates obtained with different sampling schemes were then compared with those obtained from litter collection measurements.
Results
Large differences were observed for all four variable estimates (i.e. gap fraction, Ω e , PAI e and LAI) under different sampling schemes. The differences in impact of sampling schemes on LAI estimation were not obvious for the three inversion models, if the four Ω e algorithms, except for the traditional gap-size analysis algorithm were adopted in the estimation. The accuracy of LAI estimation was not always improved with an increase in sample size. Moreover, results indicated that with the appropriate inversion model, Ω e algorithm and sampling scheme, the maximum estimation error of DHP-estimated LAI at elementary sampling unit can be less than 20%, which is required by the global climate observing system, except in forest plots with extremely large LAI values (~ > 6.0). However, obtaining an LAI from DHP with an estimation error lower than 5% is impossible regardless of which combination of inversion model, Ω e algorithm and sampling scheme is used.
Conclusion
The LAI estimation of L . principis-rupprechtii forests from DHP was largely affected by the sampling schemes adopted in the estimation. Thus, the sampling scheme should be seriously considered in the LAI estimation. One square and two transect sampling schemes (with sample sizes ranging from 3 to 9) were recommended to be used to estimate the LAI of L . principis-rupprechtii forests with the smallest mean relative error (MRE). By contrast, three cross and one dispersed sampling schemes were identified to provide LAI estimates with relatively large MREs.
... The LAI can be measured directly by leaf harvesting and indirectly using digital plant canopy analyzer (Ryu et al., 2010;Majasalmi et al., 2013), destructive sampling (Mason et al., 2012), and litter collection methods (Cutini et al., 1998;Ishihara and Hiura, 2011). The litterfall collection method is more commonly used in deciduous forests than Fig. 1. ...
... Location of study area and patterns of monthly temperature and rainfall at Ukhimath Central Himalaya. R.K. Joshi and S.C. Garkoti Ecological Indicators 111 (2020) 106065 evergreen forests (Cutini et al., 1998;Nasahara et al., 2008). For estimating the LAI, leaf dry mass at each sampling date was converted into leaf area by multiplying the leaf biomass from the litter traps (g m −2 ) with a specific leaf area (SLA cm 2 g −1 ). ...
... Asner et al. (2003) carried out a global LAI review based on more than a thousand studies, in which the works in Brazil were concentrated in the Amazon region. The literature has presented LAI values greater than 2.00 m 2 m −2 and less than 7.00 m 2 m −2 for deciduous forests (Dufrêne and Bréda, 1995;Cutini et al., 1998;Kalacska et al., 2005). Asner et al. (2003) observed in their work that the LAI of deciduous forests showed an average value of 3.90 m 2 m −2 and a standard deviation of 2.50 m 2 m −2 . ...
... The small temporal variability of the maximum LAI is probably attributable to the stability in the vegetation pattern in the AEB, which is part of the Aiuaba Ecological Station, created in 1978 and preserved ever since. Other studies have shown that, over time, the temporal differences of LAI decrease until they reach their stability with the climax of the vegetation (Cutini et al., 1998;Creutzfeldt, 2006;Pinheiro et al., 2016). In a study evaluating above and below-ground biomass in the secondary rain forest, Kenzo et al. (2010) found that, when forests aged from 4 to 10 years, the LAI increased intensively (it doubled within six years); however, when it aged from 10 to 17 years, the forests Fig. 3. Performance of hydrological variables to estimate the leaf area index (LAI) in comparison to the measured value for soil-vegetation association 2 (SVA2) and for the whole Aiuaba Experimental Basin (AEB). ...
... Within the entire LAI estimation procedure using litter traps, a precise estimation of the SLA is the most critical point 10 because the SLA can vary with plant species 65 , date and year, length of time in the traps, weather 66 , and site fertility 67 . Although litter traps are usually considered as the reference level, and a calibration tool for indirect methods 38,49 , a possible discrepancy of LAI estimation using litter traps can occur due to wind flow, the number and distribution of the traps within the stand regardless of canopy cover and stand structure, the size of the stand area, 68,69 or it can also be caused by a deflection of the litter trap from its level, horizontal position. Furthermore, LAI values obtained by litter traps can also be affected by weather and climate 70 , especially by decomposition of the litter-fall 10,11 or the withering of leaves in traps, which can be elicited by severe drought during summer months. ...
... The use of the plant canopy analyzer to estimate the WAI in leafless periods and its subtraction from optical PAI (i.e., effective plant area index) in leafy period seems to be practical 72 . In contrast, the potential of this instrument is restricted by its general tendency towards underestimating LAI in discontinuous and heterogeneous canopies 15,20,43,49,74 which is mainly ascribed to the contribution of woody materials and clumping effects within the canopy 10,72 . On the contrary, overestimation of the LAI can be observed in stands composed of species (e.g., poplar) that can replace their leaves during the growing season 11 . ...
Accurate estimations of leaf area index (LAI), defined as half of the total leaf surface area per unit of horizontal ground surface area, are crucial for describing the vegetation structure in the fields of ecology, forestry, and agriculture. Therefore, procedures of three commercially used methods (litter traps, needle technique, and a plant canopy analyzer) for performing LAI estimation were presented step-by-step. Specific methodological approaches were compared, and their current advantages, controversies, challenges, and future perspectives were discussed in this protocol. Litter traps are usually deemed as the reference level. Both the needle technique and the plant canopy analyzer (e.g., LAI-2000) frequently underestimate LAI values in comparison with the reference. The needle technique is easy to use in deciduous stands where the litter completely decomposes each year (e.g., oak and beech stands). However, calibration based on litter traps or direct destructive methods is necessary. The plant canopy analyzer is a commonly used device for performing LAI estimation in ecology, forestry, and agriculture, but is subject to potential error due to foliage clumping and the contribution of woody elements in the field of view (FOV) of the sensor. Eliminating these potential error sources was discussed. The plant canopy analyzer is a very suitable device for performing LAI estimations at the high spatial level, observing a seasonal LAI dynamic, and for long-term monitoring of LAI.
... The leaves were then oven-dried for 24 hours at 70°C to estimate their dry weight. Specific leaf area (SLA) was calculated by dividing leaf area by leaf dry mass (cm 2 g-1 ) (Cutini et al 1998). The water content percentage was calculated as: ...
Atriplex halimus is a widely distributed species in the Mediterra-nean coastal areas and can grow in saline and non-saline habitats. Plant leaves were collected from two habitats, non-saline (1.14 dSm-1) and saline (30.63 dSm-1) at Borg Alarab area on the NorthWestern coast of Egypt, to investigate the eco-morphological and physiological behaviour variations of A. halimus under different habitats. Leaf area and specific leaf area (SLA) were measured while moisture, chlorophylls a and b, carotenoids, Na + , K + , Ca ++ and Cl-contents were determined. A. halimus leaves generate adaptive changes as plastic responds to salinity by reducing leaf area, SLA, chloro-phylls a and b, and Cl contents but expressed an increase of phenyl-alanine ammonia-lyase (PAL) specific activity as well as Na + and total phenol contents .
... The leaves were then oven-dried for 24 hours at 70°C to estimate their dry weight. Specific leaf area (SLA) was calculated by dividing leaf area by leaf dry mass (cm 2 g-1 ) (Cutini et al 1998). The water content percentage was calculated as: ...
... While the former includes field observations, surveys, and litter harvesting; however, these methods are time-consuming, less costeffective, laborious, and logistically impractical, particularly within large spatial extents (Omer et al. 2016;Wang et al. 2019;Yu et al. 2019). Nevertheless, direct methods are highly accurate and can be used as a reference for developing and improving data collected through indirect methods (Cutini, Matteucci, and Mugnozza 1998). On the other hand, indirect methods include innovative approaches such as remote sensing, which can generate spatially explicit information on species; this is particularly important within a commercial forestry landscape (Peltzer et al. 2015). ...
Leaf Area Index (LAI) remains one of the most important forest structural attributes, as accurate estimation of LAI is crucial for predicting the growth of different species. Using the Partial Least Squares Regression (PLS-R) algorithm, this study investigated three image processing techniques to determine the best technique for estimating LAI using WorldView-3 imagery in the Midlands, KwaZulu-Natal province of South Africa. The PLS-R texture ratios model achieved the highest accuracy of R 2 = 0.70, RMSE = 1.21 (2.32% of the mean measured LAI) and R 2 = 0.72, RMSE = 1.26 (2.41% of the mean measured LAI) for the wet and dry seasons, respectively. This was followed by the PLS-R single texture band model that produced an accuracy of R 2 = 0.65, RMSE = 1.35 (2.58% of the mean measured LAI) and R 2 = 0.67, RMSE = 1.32 (2.52% of the mean measured LAI) for the wet and dry seasons, respectively. The PLS-R model using a combination of vegetation indices had the lowest estimation accuracy of R 2 = 0.59, RMSE = 1.38 (2.64% of the mean measured LAI) and R 2 = 0.60, RMSE = 1.40 (2.67% of the mean measured LAI) for the wet and dry seasons, respectively. The results of this study provided evidence that image texture ratios can be used to estimate LAI effectively.
... A leaf area index (LAI) is defined as half of the leaf surface area per unit area and plays a critical role in ecological and agricultural research [1][2][3]. Long-term measurements of LAI are of great significance for studying climate change, ecosystems, and crop growth [4][5][6][7][8]. ...
The leaf area index (LAI) is one of the core parameters reflecting the growth status of vegetation. The continuous long-term observation of the LAI is key when assessing the dynamic changes in the energy exchange of ecosystems and the vegetation’s response indicators to climate change. The errors brought about by non-standard operations in manual LAI measurements hinder the further research utilization of this parameter. The long-term automatic LAI observation network is helpful in reducing errors from manual measurements. To further test the applicability of automatic LAI observation instruments in forest environments, this study carried out comparative validation research of the LAI-NOS (LAI automatic network observation system) at the Wanglang Mountain Ecological Remote Sensing Comprehensive Observation Station, China, comparing it with the results measured by the LAI-2200 Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA), the LAI-probe handheld instrument, and a fisheye lens digital camera (DHP method). Instead of using the original “smoothest window” method, a new method, the “sunrise–sunset” method, is used to extract daily LAI-NOS LAI, and the corresponding confidence level is used to filter the data. The results of the data analysis indicate the following: LAI-NOS has a high data stability. The automatically acquired daily data between two consecutive days has a small deviation and significant correlations. Single-angle/multi-angle LAI measurement results of the LAI-NOS have good correlations with the LAI-2200 (R² = 0.512/R² = 0.652), the LAI-probe (R² = 0.692/R² = 0.619), and the DHP method (R² = 0.501/R² = 0.394). The daily LAI obtained from the improved method, when compared to the original method, both show the same vegetation growth trend. However, the improved method has a smaller dispersion. This study confirms the stability and accuracy of automatic observation instruments in mountainous forests, demonstrating the distinct advantages of automatic measurement instruments in the long-term ground observation of LAIs.
... Conversely, positive correlations have been proved between increment and irradiance (Monteith 1972;Aldea et al. 2017), as well as with precipitation (Michelot et al. 2012;Sohar et al. 2014;Aldea et al. 2017) and the amount of live foliage in the ecosystem, which is the "production unit" of the stand (Černý et al. 2020;Parker 2020;Černý & Pokorný 2021). In fully stocked undefoliated oak stands, the maximum leaf area index (LAI) value ranges from 2.2-6.0 m 2 m −2 in production forests (Bequet et al. 2012;Černý et al. 2019) and around 7 m 2 m −2 in natural forests (Cutini et al. 1998;Čermák 1998;Glathorn et al. 2017). ...
This paper provides characteristic and a comprehensive overview of the adaptation strategies of sessile oak (Quercus petraea [Matt.] Liebl.) in the context of global climate change (GCC). The GCC is primarily manifested by increasing air temperatures and changing precipitation distribution. It poses a significant challenge to tree species including sessile oak, affecting its capacity for adaptation and survival. Despite the challenge, sessile oak shows significant drought tolerance due to its deep-reaching root system, which allows the tree to use available water more efficiently. Other adaptive strategies include the establishment of mixed stands that increase the resilience and biodiversity of the ecosystem. Adjustments of stand density through tending interventions play a significant role, helping to improve the stress resistance of stands. Additionally, coppice forest cultivation is applied on extremely dry sites. The sessile oak is also significant for its ecological plasticity-its ability to thrive on versatile soil and climatic conditions makes it a promising tree species for future forest management. Mixed stands with sessile oak and other tree species can enhance the ecosystem services of forests and also increase their endurance to GCC events. However, sessile oak faces several challenges, including the increasing risk of damage from pests and pathogens that require targeted measures for its protection and sustainable cultivation. The literature review suggests that a comprehensive understanding of sessile oak's ecological requirements and interactions with the environment is crucial for its successful adaptation to GCC and the formulation of effective strategies for its protection and use in forest management.
... We used LI-COR LAI-2200c Plant Canopy Analyzer to perform non-destructive LAI measures. The instrument is equipped with a fisheye lens and detects light interception in five concentric sky sectors (Cutini et al. 1998); LAI is computed by comparing the diffuse radiation underneath the canopy to measures taken in large clearings with no light-blocking objects (Breda 2003;Danner et al. 2015). Following the recommendations by LI-COR, we used the single sensor, scattering correction procedure, which is required for direct sunlight conditions. ...
Background
Leaf area index (LAI) is a key indicator for the assessment of the canopy’s processes such as net primary production and evapotranspiration. For this reason, the LAI is often used as a key input parameter in ecosystem services’ modeling, which is emerging as a critical tool for steering upcoming urban reforestation strategies. However, LAI field measures are extremely time-consuming and require remarkable economic and human resources. In this context, spectral indices computed using high-resolution multispectral satellite imagery like Sentinel-2 and Landsat 8, may represent a feasible and economic solution for estimating the LAI at the city scale. Nonetheless, as far as we know, only a few studies have assessed the potential of Sentinel-2 and Landsat 8 data doing so in Mediterranean forest ecosystems. To fill such a gap, we assessed the performance of 10 spectral indices derived from Sentinel-2 and Landsat 8 data in estimating the LAI, using field measurements collected with the LI-COR LAI 2200c as a reference. We hypothesized that Sentinel-2 data, owing to their finer spatial and spectral resolution, perform better in estimating vegetation’s structural parameters compared to Landsat 8.
Results
We found that Landsat 8-derived models have, on average, a slightly better performance, with the best model (the one based on NDVI) showing an R2 of 0.55 and NRMSE of 14.74%, compared to R2 of 0.52 and NRMSE of 15.15% showed by the best Sentinel-2 model, which is based on the NBR. All models were affected by spectrum saturation for high LAI values (e.g., above 5).
Conclusion
In Mediterranean ecosystems, Sentinel-2 and Landsat 8 data produce moderately accurate LAI estimates during the peak of the growing season. Therefore, the uncertainty introduced using satellite-derived LAI in ecosystem services’ assessments should be systematically accounted for.
... Der Blattflächenindex, der in diesen Untersuchungen mit Hilfe des LAI-Meters Es hat sich gezeigt, dass verschiedene Messeverfahren zur Bestimmung des Blattflächenindexes erhebliche Unterschiede in den Ergebnissen zur Folge haben können. Cutini et al. (1998) Die maximalen Saftflüsse erreichen Werte von 0,4 ml*cm -2 *min -1 bei den Eichen und 0,3 ml*cm -2 *min -1 bei den Eschen. Abgesehen von diesen Spitzenwerten liegt der maximale tägliche Saftfluss meist zwischen 0,1 ml*cm -2 *min -1 und 0,2 ml*cm -2 *min -1 . ...
... Further, previous literature has made it clear that the LAI-2000 underestimates the overall canopy PAI (for a general discussion on the topic, see Stenberg 1996). For example, measurements from Pokorný and Marek (2000) showed an underestimation of PAI up to 15% for spruce stands, whereas direct measurement techniques employed by Cutini et al. (1998) showed an underestimation of PAI up to 26.5% for deciduous forests. Finally, the theory developed mainly by Ross (Ross 1981) confirms the above observations (see Sect. 2.5 for an extensive discussion on this topic). ...
Although the fidelity of computational-fluid-dynamics (CFD) models for the study of flow in plant canopies has significantly increased over the past decades, the inability to exactly measure the canopy structure and its material and physiological properties introduces a degree of uncertainty in model results that is often difficult to quantify. The present work addresses this problem by proposing a Bayesian uncertainty quantification (UQ) framework for evaluating the impact of uncertain canopy geometry on selected microscale flow statistics (the quantities of interest, QoIs, of the problem). The framework links available in-situ measurements of flow statistics to the uncertainty stemming from foliage spatial distribution and orientation, as well as from the aerodynamic plant response. The uncertainty is first characterized via a Markov chain Monte Carlo procedure, and then propagated to the QoIs through the Monte Carlo sampling method, which returns mean profiles and two-standard-deviation-(2SD-)intervals for the QoIs. The UQ framework relies on a one-dimensional CFD solver to simulate the flow over the Duke Forest, located near Durham, North Carolina, USA. Model results are compared against a standard deterministic solution in terms of mean velocity, Reynolds stress and turbulence-kinetic-energy profiles, as well as canopy aerodynamic parameters. For the considered QoIs, it is found that the 2SD-intervals obtained with the UQ procedure cover 80% of the experimental intervals, whereas the deterministic solution overlaps with only 47% of them. Overall, this study highlights the potential of UQ to advance CFD capabilities for predicting exchange processes between realistic plant canopies and the surrounding atmosphere.
... Indirect measurements should be based on certain assumptions, such as the spatial distribution of the leaves following Poisson distribution and the leaves being completely opaque. However, actual vegetation canopies do not satisfy these assumptions in most cases due to a variety of complex factors, such as the clumping effect and leaf inclination distribution, and the LAI measurement error introduced by this method can reach 30− 70% (Chen and Cihlar, 1995;Cutini et al., 1998;Fang et al., 2014;Gower et al., 1999). The clumping index uses the ratio of the LAI measurement value to the actual LAI value under ideal assumptions and improves the measurement accuracy to some extent. ...
The leaf area index (LAI) is an important indicator reflecting the growth status of vegetation and is widely used in agriculture, ecology, climate change, and other fields. The shortcomings of the currently available methods for manually measuring LAI include labor-intensive, low sampling frequency, and asynchronous data collection. Focusing on these issues, a LAI sensor based on hemispherical photogrammetry and an automatic network observation system (LAI-NOS) for LAI were developed, which consists of four parts: LAI sensor, sensor node, sink node, and online data management system. The LAI sensor measures LAI values based on hemispherical photography. The sensor node is responsible for controlling the sensor and obtaining the data measured by the LAI sensor. The sink node is responsible for local networking and communication with the remote server. Data storage, data management, data display, and sampling frequency are managed by the online data management system. Comparative studies with LAI-2200C and satellite products were also conducted in this study. The comparative study with LAI-2200C showed that the LAI measurements of different vegetation types from both sources were highly significantly correlated whether based on Pearson regression or Passing & Bablok regression. A preliminary study comparing LAI-NOS measurements with Sentinel-2 inversion LAI and MODIS LAI products (MOD15A2H) showed (1) all LAI-NOS nodes measurements agreed very well with Sentinel-2 inversion LAI in the experimental period (average R²=0.94, RMSE=0.41); (2) the possible overestimate of Sentinel-2 inversion LAI was found in the middle stage of wheat (jointing-anthesis); (3) MOD15A2H and LAI-NOS measurements showed similar crop growth trends in long-term observations.
... Satellite LAI values used in this study were compared with field measurements with an overestimation of 20% considering all LCTs (Figure 4). Deciduous broadleaves and Holm oak forests showed the highest LAI values (4.12 and 4.41, respectively; statistics are shown in Table S2), in accordance with what was previously found for Deciduous oaks stands [78]. We measured lower LAI values for Pine forests and Mediterranean maquis (2.08 and 3.85, respectively), in line with previous findings [79,80]. ...
Mediterranean coastal areas are among the most threated forest ecosystems in the northern hemisphere due to concurrent biotic and abiotic stresses. These may affect plants functionality and, consequently, their capacity to provide ecosystem services. In this study, we integrated ground-level and satellite-level measurements to estimate the capacity of a 46.3 km² Estate to sequestrate air pollutants from the atmosphere, transported to the study site from the city of Rome. By means of a multi-layer canopy model, we also evaluated forest capacity to provide regulatory ecosystem services. Due to a significant loss in forest cover, estimated by satellite data as −6.8% between 2014 and 2020, we found that the carbon sink capacity decreased by 34% during the considered period. Furthermore, pollutant deposition on tree crowns has reduced by 39%, 46% and 35% for PM, NO2 and O3, respectively. Our results highlight the importance of developing an integrated approach combining ground measurements, modelling and satellite data to link air quality and plant functionality as key elements to improve the effectiveness of estimate of ecosystem services.
... Direct methods for field data collection have been commonly used to obtain vegetation information (Cutini et al., 1998). However, these methods are costly. ...
Vegetation cover maps across ecologically-fragile and particularly arid and semi-arid forest ecosystems are prerequisites for their monitoring and management. Direct and field-based measurements of vegetation cover pose serious challenges due to high costs and inaccessibility in harsh terrains, whereas multispectral remote sensing offers objective, spatially-explicit and rapid alternatives. One of the most straightforward tools is the use of broadband vegetation indices (VIs), which are mathematical derivations from multispectral bands that are correlated with various vegetation traits. There are a number of broadband VIs that reach their optimum performance by calibrating their regulatory parameters. We improved the performance of selected VIs for both greenness estimation and land-cover classification across semi-arid woodlands by optimizing their regulatory parameters. We showed this across two separate areas in highly-fragile and sparse vegetation of Zagros mountains of Iran. Regulatory parameters were optimized by multi-objective particle swarm optimization (MOPSO) for Enhanced VI (EVI) and two innovative, more complex broadband indices that use red, blue, and near-infrared multispectral bands. Then, they were applied to estimate greenness and classify vegetation, and were validated by subsets of very high-resolution optical imagery. The results suggest high accuracy of these indicators for estimating and classifying vegetation compared with the commonly-used broadband VIs. Amongst the improved VIs, the one with a more complex combination of spectral bands comparatively returned the best performance, that was 1.34× and 1.33× higher in greenness estimation and 1.58× higher in classification compared with the benchmark NDVI. They also described a higher variance across systematic transects in both regions. In conclusion, both greenness estimation and classification of semi-arid, sparse woodlands were more accurate by optimizing their regulatory parameters.
... The LAI e field results presented here are a reference for this species in the study area in that they consider different forest management activities (thinning intensities). The values for LAI e found in this work are similar to those found in studies based on deciduous forests of other species, although none of them consider management activities (Cutini et al. 1998;Le Dantec et al. 2000). The results presented here are, however, in line with a previous study of forest management in the study area in terms of LAI e values (Prada et al. 2020). ...
The Leaf Area Index (LAI) is a key parameter that helps to understand the connection between canopy structure and ecosystem functions. In this study, the main aims were to examine the impact of forest management on canopy structure using LiDAR data to characterize the canopy vertical profile, as well as to develop LAI models and an LAI mapping tool for sweet chestnut (Castanea Sativa Mill.) coppice. Twenty-one circular plots (r = 10 m) were established, each of which was submitted to one of the following forest management treatments: Control, with no intervention (3300–3700 stems ha⁻¹); Treatment 1, one thinning to leave a living stock density of 900–600 stems ha⁻¹; or Treatment 2, a more intensive thinning, leaving 400 stems ha⁻¹. A LAI field measurement was made in all plots and the study area was recorded by LiDAR. With the LiDAR, two types of metrics were calculated: standard elevation metrics and canopy metrics. The results showed the different canopy layers of the study area, highlighting how the resprout layer influences the canopy structure of sweet chestnut coppice. By combining the LiDAR data and the LAI field estimates, various linear and nonlinear models were developed and tested, the linear model being found to have the best performance (R² = 0.79) for the study area. With the selected linear model and other LiDAR data of interest such as the 95th percentile, an automatic mapping tool was designed. This tool allows spatially information to be generated that can be used to implement management strategies.
... Canopy and tree or shrub characteristics were quantified. Uncorrected leaf area index (LAI) was quantified by light attenuation using paired canopy analyzers (LAI-2000, LI-COR, Lincoln, NE) with 76 • view angles (Cutini et al., 1998), which yields reasonable relativistic values in baldcypress swamps (Allen et al., 2015). Measurements were taken on an approximately 6m interval over the length of the boardwalk (88 measurements) in July 2015 (Figure 1). ...
Compared to leaves, bark is under-studied with regards to its role in the water cycle. This is an important knowledge gap as, unlike leaves, bark is ever-present in forest ecosystems and can represent a significant interface for water interaction. Bark is also porous, hygroscopic, present in litter layers from shedding, as well as on fallen woody debris, and performs a multitude of ecophysiological functions. Finally, considering the particulates, organisms, and leachable/washable solutes present on and in bark, many opportunities may exist for improving forest ecohydrological understanding through the research of bark-water interactions. Thus, this collection contains articles that highlight bark interactions with various hydrologic processes and related ecological processes.
... While surface area data have long been available for leaves (Lindsey and Bassuk 1992, Cutini et al. 1998, Reich 2001, Chianucci et al. 2019, TLS, in combination with QSMs, can now be used to quantify the surface area of the "woody skeleton" of trees, which plays a vital role in gas exchange with the atmosphere. Tree respiration rates are closely related to their WSA , Bosc et al. 2003) because respiration of nonphotosynthetic tissues mainly occurs in the cambial sheath and the living annual growing rings around the dead heartwood . ...
The study of the architecture of urban trees is important for the management of urban forests to optimize their ecological and socioeconomic services. Trees have a fractal-like architecture which is disrupted by competition for light. Therefore, studying the architecture of open-grown urban trees should provide a better understanding of the inherent fractal-like character of trees. Terrestrial Laser Scanning (TLS) technology provides detailed data of tree architecture. The main scope of this dissertation was to model the fractal-structural complexity of urban trees based on different fractal analysis methods in relation to their physiological and functional traits.
In the second chapter of the dissertation, a variant of the "two-surface" method was used to estimate the fractal dimension of thousands of urban tree crowns from a publicly-available dataset across the USA. It was found that urban trees reduced their crown fractal dimension to reduce water loss through transpiration in hotter cities depending on the level of urbanization at smaller spatial scales. The functional group and the life-history traits of the studied urban trees significantly affected their crown fractal dimension in response to their growing environment.
In the third chapter, forty-five trees of different deciduous species (Gleditsia triacanthos L., Quercus macrocarpa Michx., Metasequoia glyptostroboides Hu & W.C. Cheng) were laser scanned in leaf-on and -off conditions on the Michigan State University campus to study the role of leaves in the fractal-structural complexity of urban trees using the "box-dimension" (Db) metric. It was found that the presence of leaves significantly increased the Db metric of all study trees, and the contribution of leaves decreased as branch network complexity increased. The leaf-on laser point clouds of the study trees were also virtually defoliated with a leaf-removal algorithm. It was found that the algorithmic leaf-removal caused biased estimates of the Db of the G. triacanthos and M. glyptostroboides trees.
In the fourth chapter, the leaf-off laser point clouds of fifty-six urban trees of the aforementioned species were used to generate quantitative structural models (QSMs) to quantify their woody surface area (WSA) allometry. It was found that the variation in the above-ground WSA of the study trees related to their fractal dimension quantified with the Db metric and the distribution of "path" lengths from the tree base to every branch tip. It was also found that the urban trees allocated the largest portion of their WSA to their branches, which varied with branch order, branch-base diameter, and branch-base height. This study also showed a positive relationship between the WSA and the crown surface area of the urban trees.
The fifth chapter included laser point clouds of thirty-one trees of deciduous and evergreen species that were sampled on the Michigan State University campus and the Harvard Forest in Petersham, MA, USA to model their above-ground woody biomass. QSMs were generated to estimate the total tree volume and component volumes of the study trees. Biomass estimates were produced by multiplying the TLS-based volumes with measurements of tree basic density from sample disks from stems and branches obtained after destructively sampling the trees, and also with published basic density values at species level. The leaves of the trees that were scanned in leaf-on condition were artificially removed before QSM generation. It was found that TLS technology can be used to produce reliable total and component biomass estimates of trees. The biomass estimates quality can be affected by the growing environment, the leaf condition of the laser-scanned trees and the basic density values that are used.
... While surface area data have long been available for leaves [101][102][103][104][105][106][107][108], TLS, in combination with QSMs, can now be used to quantify the surface area of the "woody skeleton" of trees, which plays a vital role in gas exchange with the atmosphere. Tree respiration rates are closely related to their WSA [18][19][20] since respiration of non-photosynthetic tissues mainly occurs in the cambial sheath and the living annual growing rings around the dead heartwood [17]. ...
Urban forests are part of the global forest network, providing important benefits to human societies. Advances in remote-sensing technology can create detailed 3D images of trees, giving novel insights into tree structure and function. We used terrestrial laser scanning and quantitative structural models to provide comprehensive characterizations of the woody surface area allometry of urban trees and relate them to urban tree anatomy, physiology, and structural complexity. Fifty-six trees of three species (Gleditsia triacanthos L., Quercus macrocarpa Michx., Metasequoia glyptostroboides Hu & W.C. Cheng) were sampled on the Michigan State University campus. Variations in surface area allocation to non-photosynthesizing components (main stem, branches) are related to the fractal dimension of tree architecture, in terms of structural complexity (box-dimension metric) and the distribution of “path” lengths from the tree base to every branch tip. The total woody surface area increased with the box-dimension metric, but it was most strongly correlated with the 25th percentile of path lengths. These urban trees mainly allocated the woody surface area to branches, which changed with branch order, branch-base diameter, and branch-base height. The branch-to-stem area ratio differed among species and increased with the box-dimension metric. Finally, the woody surface area increased with the crown surface area of the study trees across all species combined and within each species. The results of this study provide novel data and new insights into the surface area properties of urban tree species and the links with structural complexity and constraints on tree morphology.
... In addition, Leaf Area Index (LAI) (m 2 /m 2 ) is a key index, as it correlates with the water, energy, and CO 2 exchange potentials of a vegetative ecosystem and the atmosphere (Korhonen et al., 2011). LAI showcases the ratio of the green surface area to the soil or ground surface area (Cutini et al., 1998). Thus, LAI can effectively illustrate the change of vegetative surfaces with regard to wet and dry environmental conditions (Mafi-Gholami et al., 2019). ...
Changes of biophysical and biochemical features in canopy cover over space and time can be used to elucidate watershed resilience to climate change or extreme weather. Geospatial technologies such as satellite remote sensing are helpful to identify such vegetation dynamics. This paper investigates the landfall impact of Hurricane Irma on canopy cover in the Santa Fe River Basin (Florida), which occurred in August 2017. Specifically, this study explores the effect of Hurricane Irma on vegetation dynamics via biophysical and biochemical features during the pre and post hurricane landfall. The geospatial analysis compares a suite of remote sensing spectral indices including enhanced vegetation index (EVI), leaf area index (LAI), fraction of photosynthetically active radiation (FPAR), evapotranspiration (ET), land surface temperature (LST), and global vegetation moisture index (GVMI). It is noticeable that paired spectral indices such as EVI-LST, GVMI-LST, LAI-LST, EVI-GVMI, EVI-LAI, LAI-FPAR, EVI-FPAR, and LAI-GVMI reflecting the dependent relationships between biophysical and biochemical features reveal varying level of logistic trends under Irma landfall impact. In addition, the evolution of these biophysical and biochemical features associated with the vegetation cover was analyzed in terms of the functional capacity over grassland, evergreen forested land, deciduous forested land, and agricultural land, to understand watershed response following Irma landfall. The functional capacity of the ecosystem reduced in terms of EVI and LAI over these four land-over patterns due to the landfall of Hurricane Irma. The interactions between agricultural land variation and flooding impact before and after the hurricane landfall further entail human impact on natural system in a food-water nexus.
... Canopy and tree or shrub characteristics were quantified. Uncorrected leaf area index (LAI) was quantified by light attenuation using paired canopy analyzers (LAI-2000, LI-COR, Lincoln, NE) with 76 • view angles (Cutini et al., 1998), which yields reasonable relativistic values in baldcypress swamps (Allen et al., 2015). Measurements were taken on an approximately 6m interval over the length of the boardwalk (88 measurements) in July 2015 (Figure 1). ...
The interception of precipitation by plant canopies can alter the amount and spatial distribution of water inputs to ecosystems. We asked whether canopy interception could locally augment water inputs to shrubs by their crowns funneling (freshwater) precipitation as stemflow to their bases, in a wetland where relict overstory trees are dying and persisting shrubs only grow on small hummocks that sit above mesohaline floodwaters. Precipitation, throughfall, and stemflow were measured across 69 events over a 15-months period in a salinity-degraded freshwater swamp in coastal South Carolina, United States. Evaporation of intercepted water from the overstory and shrub canopies reduced net precipitation (stemflow plus throughfall) across the site to 91% of gross (open) precipitation amounts. However, interception by the shrub layer resulted in increased routing of precipitation down the shrub stems to hummocks – this stemflow yielded depths that were over 14 times larger than that of gross precipitation across an area equal to the shrub stem cross-sectional areas. Through dimensional analysis, we inferred that stemflow resulted in local augmentation of net precipitation, with effective precipitation inputs to hummocks equaling 100–135% of gross precipitation. Given that these shrubs (wax myrtle, Morella cerifera) are sensitive to mesohaline salinities, our novel findings prompt the hypothesis that stemflow funneling is an ecophysiologically important mechanism that increases freshwater availability and facilitates shrub persistence in this otherwise stressful environment.
... method. In contrast to litter traps, which are considered one of the ost accurate methods for performing LAI estimation (Cutini et al., 1998), we achieved dynamic prediction of the LAI of each species by ensuring accuracy. Moreover, the proposed model benefits from the DBH-LN allometric model of the three species and requires only a simple plot investigation and calculation of the average single leaf area, which implies that estimating the LAI of this species eliminates stand restrictions. ...
Global warming is causing substantially earlier spring leaf phenology in temperate‐zone trees. Understanding the drivers and mechanisms behind the observed plant phenological changes is important for predicting future phenological dynamics. Here, leaf phenological dynamic data (including number and area) observed in situ for three tree species (namely, Tilia amurensis, Pinus koraiensis and Betula platyphylla) on Changbai Mountain from 2017 to 2020 were analyzed. We found that none of the tree species showed active accumulated temperature (AAT) differences in phenological events and phase; however, differences in time (i.e., photoperiod) were observed and could be explained by AAT being the primary controller of plant phenology. Moreover, we developed process-based spring leaf phenology models that were fitted and validated using the leaf development process and time series. Compared with the time-based models, the phenology model with AAT as the independent variable is more robust in fitting and predicting leaf area and leaf number. Our novel findings provide evidence of AAT effects on leaf unfolding, whereby when the AAT reaches a certain threshold, the corresponding phenology will be triggered. Therefore, we used AAT-based models and plot survey data to simulate the leaf area index (LAI) dynamics of the tree species studied, which provides a feasible method to understand the complex processes scaling up from the plant and forest‐levels. Our study has provided a new answer to how temperature affects spring leaf phenology in temperate forests, and significantly improved the predictability for leaf development.
... The first is direct measurement through destructive sampling, which is time-consuming and laborious but relatively accurate (Lang, 1991;Deblonde et al., 1994). The second is the optical measurement at the leafless stage, and then use the PAI value measured at the leafy stage and the WAI value measured at the leafless stage to obtain the α value (Cutini et al., 1998;Barclay et al., 2000). This method has higher efficiency than the direct method, but it does not take into account mutual occlusion between woody and foliar materials and it is also not suitable for evergreen forests (Zou et al., 2009). ...
Automatic and accurate measurements of the leaf area index (LAI) can provide information about key parameters of vegetation structure in an ecosystem. Little attention, however, has been paid to LAI dynamics for shrub canopies in both arid and semiarid regions compared to forests and crops. One of the main sources of error when measuring shrub LAI from the indirect method is the woody part. The influence of woody parts on LAI estimations can be expressed as the woody-to-total area ratio, α; there are also relatively few studies on α value of shrubs, especially the dynamic changes of α. This study used a new cost-effective tool, the fisheye webcam, to derive daily LAI and α in the fields of Caragana korshinskii and Salix psammophila on the Loess Plateau in China. The LAI data were compared with measurements acquired by an LAI-2200 Plant Canopy Analyzer and direct methods. The LAI-2200 data were consistent with the effective plant area index (PAIeff) estimated using upward-pointing webcams (UPWs) (R² = 0.89, root mean square error (RMSE) = 0.21) but not downward-pointing webcams (DPWs) (R² = 0.52, RMSE = 0.68). Shrub PAIeff derived from the DPWs was much smaller than PAIeff derived from the UPWs over the season (y = 0.48x–0.03, R² = 0.79, RMSE = 0.85). LAI derived from the direct methods was strongly linearly correlated with the PAI minus WAI obtained from upward digital hemispherical photography (R² = 0.94, RMSE = 0.62 for C. korshinskii and R² = 0.99, RMSE = 0.31 for S. psammophila). This result indicates that the upward digital hemispherical photography for deriving PAI and WAI performs good, which can be utilized to calculate LAI accurately. The woody-to-total area ratio (α) of deciduous shrub canopies was a dynamic parameter that varied throughout the season, decreasing as the canopy leaves developed and increasing when they fell. α = 1 for the leaf-off season and < 0.1 when the foliage peaked. α differed little between the two shrub canopies (R² = 0.95, RMSE = 0.07), and it could be used to convert PAI to LAI for C. korshinskii and S. psammophila. The UPWs demonstrated excellent potential for continuous LAI measurement for the two shrub canopies, but the DPWs should be further tested before use. The fisheye-webcam is inexpensive and can easily monitor LAI at field scale and can be used to evaluate LAI products derived from remote sensing.
... To date, several techniques have been used to assess the share of incoming solar radiation under plant canopies. For the direct measurement of the light conditions different types of pyranometers were applied, while for indirect measurements devices such as the LAI-2000 Plant Canopy Analyser can be used to gather information about the leaf area index (LAI) of trees and forests [12]. ...
Reduced solar radiation brought about by trees on agricultural land can both positively and negatively affect crop growth. For a better understanding of this issue, we aim for an improved simulation of the shade cast by trees in agroforestry systems and a precise estimation of insolation reduction. We present a leaf creation algorithm to generate realistic leaves to be placed upon quantitative structure models (QSMs) of real trees. Further, we couple it with an enhanced approach of a 3D model capable of quantifying shading effects of a tree, at a high temporal and spatial resolution. Hence, 3D data derived from wild cherry trees (Prunus avium L.) generated by terrestrial laser scanner technology formed a basis for the tree reconstruction, and served as leaf-off mode. Two leaf-on modes were simulated: realistic leaves, fed with leaf data from wild cherry trees; and ellipsoidal leaves, having ellipsoids as leaf-replacement. For comparison, we assessed the shading effects using hemispherical photography as an alternative method. Results showed that insolation reduction was higher using realistic leaves, and that the shaded area was greater in size than with the ellipsoidal leaves or leaf-off conditions. All shading effects were similarly distributed on the ground, with the exception of those derived through hemispherical photography, which were greater in size, but with less insolation reduction than realistic leaves. The main achievements of this study are: the enhancement of the leaf-on mode for QSMs with realistic leaves, the updates of the shadow model, and the comparison of shading effects. We provide evidence that the inclusion of realistic leaves with precise 3D data might be fundamental to accurately model the shading effects of trees.
... As discussed by Chen (1996), to obtain LAI based on indirect measurements, calculations must be corrected for both the light interception by stems and branches and the non-random distribution of canopy elements (clumping). In leafless periods, optical methods can also be used to estimate woody area index (WAI) (Chason et al., 1991;Cutini et al., 1998), i.e. the total one-sided woody area per unit ground area. ...
Digital hemispherical photography (DHP) is widely used to measure the radiative environment and estimate sky view factors (SVF) in urban areas and leaf area index (LAI) in forests. However, a limitation is the difficulty to distinguish trees from buildings, or leaves from stems and branches. In this study, we collected and processed dual-wavelength photographs recording visible and near-infrared (NIR) light in order to classify pixels into sky, green and woody plant elements, and buildings. Three applications of the method are presented: calculation of partial SVFs accounting for the obstruction of sky by buildings and vegetation separately, the modelling of mean radiant temperature (Tmrt), and the correction of LAI estimates for light intercepted by woody elements and buildings. The obtained partial SVFs were in good agreement with values modelled based on digital surface models. Distinguishing between buildings and vegetation in the modelling of long-wave radiation fluxes in the SOLWEIG model resulted in differences in modelled Tmrt by up to 3 °C. The bias of LAI estimates in urban parks caused by the light interception by woody elements and buildings was found to be relatively small (3–4 %). However, the presented method shows a high potential for estimates of LAI of urban vegetation in densely built-up areas.
... Once the LAI of the canopy increases above 4, the Licor-based measurements of LAI start saturating. Similar observations were noted by Smith et al. (1993) and Cutini et al. (1998), where the LAI 2000 canopy analyser consistently underestimated canopy LAI. This problem of underprediction is majorly due to the assumption that leaves of the canopy are randomly distributed, which is not valid in many cases (Breda, 2003;Gower et al., 1999). ...
Leaf Area Index (LAI) is one of the most important biophysical properties of a crop, used in detecting long-term water stress, estimating biomass, and identifying crop growth stage. Remote sensing based LAI estimation techniques perform well for early growth stages but tend to produce high error during the crop reproductive stage due to canopy closure. Moreover, estimation of the true LAI from individual leaf measurements remains a challenge. Consequently, two alternate methods have been developed and compared for estimating the LAI of a maize crop using top-of-canopy RGB images collected throughout the growing season using a hexacopter. Both methods used the RGB images to estimate the canopy height and the green-canopy cover together with a ‘vertical leaf area distribution factor’ (VLADF) from allometric relations (using crop height from RBG images and days after sowing). The first method used an empirical approach to estimate the LAI from training a linear function of the above inputs to Licor canopy analyser values of LAI. The method was trialled for a research farm located in a semi-arid area of southern peninsula India and found to have validation results with an R2 of 0.84 and RMSE of 0.36 for the unused portion of the Rabi (post-monsoon) season data of 2018–19, and R2 of 0.77 and RMSE of 0.45 for the Rabi 2019–20 season data when compared with Licor LAI values. While seemingly acceptable, the Licor canopy analyser gives a foliage area index and so the accuracy of this model was very low (R2 of 0.56 and RMSE of 1.34) when evaluated with true LAI from manual measurements of the leaf area. Consequently, a refinement was introduced using only VLADF, green-canopy cover estimates from the RBG images, and a field measured top leaf angle. The output derived from this conceptual model had an R2 of ~0.6 and RMSE of 0.73 when compared with the true LAI values. Importantly, the LAI from this conceptual model was found to be unaffected by canopy closure during the reproductive stage of the crop.
... Indirect methods based on radiation measurements are applied to measure the LAI. The indirect method is not as precise as the direct method (collect leaves and measure their area) but can easily be automated and is less expensive and complex [48]. One of the common indirect methods is the plant canopy analyzer LAI-2000 [49] or the SunScan SS1 LAI meter (Delta-T Devices Ltd., Cambridge, UK). ...
Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types.
... Another instrument for measuring conifer LAI is LAI-2000, which uses a multi-angle gap fraction to estimate LAI, unlike the smartphone-based methods that use only one zenith angle. The LAI-2000 algorithm has been widely recognized in the literature, and interested users are encouraged to find detailed information on LAI-2000 in these references [17,18]. Because LAI-2000 has been validated on a wide range of vegetation types, this research has used the LAI value from the LAI-2000 instrument as a reference to compare the two smartphone methods. ...
Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.
... Remote sensing, specifically lidar, is able to overcome many of these problems by acting as a "plumb line" penetrating into the canopy, thereby producing information from which the three-dimensional internal structure can be interrogated [58]. Although lidar data holds great potential in standardizing and mapping LAI and LADen metrics, calibration of the data is still required with coincident ground reference data, often estimated from hemispherical photographs [59] or an LAI instrument such as Li-Cor [60]. These instruments approximate LAI from gap fractions, estimated by looking up into the canopy, and actually return a plant area index (PAI), which is often substituted for LAI. ...
Establishing linkages between light detection and ranging (lidar) data, produced from interrogating forest canopies, to the highly complex forest structures, composition, and traits that such forests contain, remains an extremely difficult problem. Radiative transfer models have been developed to help solve this problem and test new sensor platforms in a virtual environment. Many forest canopy studies include the major assumption of isotropic (Lambertian) reflecting and transmitting leaves or non-transmitting leaves. Here, we study when these assumptions may be valid and evaluate their associated impacts/effects on the lidar waveform, as well as its dependence on wavelength, lidar footprint, view angle, and leaf angle distribution (LAD), by using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) remote sensing radiative transfer simulation model. The largest effects of Lambertian assumptions on the waveform are observed at visible wavelengths, small footprints, and oblique interrogation angles relative to the mean leaf angle. For example, a 77% increase in return signal was observed with a configuration of a 550 nm wavelength, 10 cm footprint, and 45° interrogation angle to planophile leaves. These effects are attributed to (i) the bidirectional scattering distribution function (BSDF) becoming almost purely specular in the visible, (ii) small footprints having fewer leaf angles to integrate over, and (iii) oblique angles causing diminished backscatter due to forward scattering. Non-transmitting leaf assumptions have the greatest error for large footprints at near-infrared (NIR) wavelengths. Regardless of leaf angle distribution, all simulations with non-transmitting leaves with a 5 m footprint and 1064 nm wavelength saw around a 15% reduction in return signal. We attribute the signal reduction to the increased multiscatter contribution for larger fields of view, and increased transmission at NIR wavelengths. Armed with the knowledge from this study, researchers will be able to select appropriate sensor configurations to account for or limit BSDF effects in forest lidar data.
... The underestimation is comparable to our study despite the different approach to the direct method. The average underestimation of the LAI 2200 PCA in comparison with litter-traps was determined by Cutini et al. (1998) to be 29.57%, and that again corresponds to our study despite the use of the different direct method. ...
The leaf area index (LAI) is one of the most common leaf area and canopy structure quantifiers. Direct LAI measurement and determination of canopy characteristics in larger areas is unrealistic due to the large number of measurements required to create the distribution model. This study compares the regression models for the ALS-based calculation of LAI, where the effective leaf area index (eLAI) determined by optical methods and the LAI determined by the direct destructive method and developed by allometric equations were used as response variables. LiDAR metrics and the laser penetration index (LPI) were used as predictor variables. The regression models of LPI and eLAI dependency and the LiDAR metrics and eLAI dependency showed coefficients of determination (R 2) of 0.75 and 0.92, respectively; the advantage of using LiDAR metrics for more accurate modelling is demonstrated. The model for true LAI estimation reached a R 2 of 0.88.
... Several direct and indirect measurements of LAI have been developed and utilized including destructive harvesting, litterfall collection and weighing, digital hemispherical photography (DHP), canopy analyzers (such as the LiCOR LAI 2000), terrestrial laser scanning (TLS), airborne lidar (light detection and ranging) and spaceborne lidar [7][8][9][10][11][12][13][14]. Each method encounters specific assumptions, limitations and obstacles. ...
Estimating leaf area index (LAI) and assessing spatial variation in LAI across a landscape is crucial to many ecological studies. Several direct and indirect methods of LAI estimation have been developed and compared; however, many of these methods are prohibitively expensive and/or time consuming. Here, we examine the feasibility of using the free image processing software CAN-EYE to estimate effective plant area index (PAIeff) from hemispherical canopy images taken with an extremely inexpensive smartphone clip-on fisheye lens. We evaluate the effectiveness of this inexpensive method by comparing CAN-EYE smartphone PAIeff estimates to those from drone lidar over a lowland tropical forest at La Selva Biological Station, Costa Rica. We estimated PAIeff from drone lidar using a method based in radiative transfer theory that has been previously validated using simulated data; we consider this a conservative test of smartphone PAIeff reliability because above-canopy lidar estimates share few assumptions with understory image methods. Smartphone PAIeff varied from 0.1 to 4.4 throughout our study area and we found a significant correlation (r = 0.62, n = 42, p < 0.001) between smartphone and lidar PAIeff, which was robust to image processing analytical options and smartphone model. When old growth and secondary forests are assumed to have different leaf angle distributions for the lidar PAIeff algorithm (spherical and planophile, respectively) this relationship is further improved (r = 0.77, n = 42, p < 0.001). However, we found deviations in the magnitude of the PAIeff estimations depending on image analytical options. Our results suggest that smartphone images can be used to characterize spatial variation in PAIeff in a complex, heterogenous tropical forest canopy, with only small reductions in explanatory power compared to true digital hemispherical photography.
... As the leaf area is determined through repeated area measurements on single leaves and area accumulation, these methods are hence considered the most accurate (Chen et al., 1997), and for that reason they are often implemented as calibration tools for indirect measurement techniques (e.g. Cutini et al., 1998). Moreover, some of the methods have the additional advantage of incorporating an evaluation of the vertical distribution of LAI within the tree crowns, though the felling and stripping of larger single trees is very labourintensive. ...
... Then, oven dried at 70°C for 24 h to determine the leaf dry weight. Specific leaf area (SLA) was calculated by the ratio between leaf area and leaf dry mass (cm 2 g -1 ) (Cutini et al. 1998). ...
Limoniastrum monopetalum is a perennial halophyte growing at different habitats along the Mediterranean Sea coast of Egypt. The morpho-anatomical and physiological responses was investigated for L. monopetalum leaves collected from; wet salt marshes, coastal sand dunes and rocky ridges habitats. The plant acquired the highest values of leaf area, lamina thickness, specific leaf area and water content despite of the high salinity in the salt marshes habitat. Additionally, plant is able to regulate content of Na+, Cl−, K+, Ca2+, Mg2+, accumulate proline and total phenols. On the other hand, plants growing in the driest habitats (coastal sand dunes and rocky ridges) acquired xeromorphic features viz., thick cuticle, compacted palisade tissue, increasing lignification of sclerified tissue and ash content. Moreover, plants in coastal sand dunes displayed extra adaptive responses viz., increase in chl. a, chl. b, carotenoids, K+ and Cl−, palisade ratio and stomatal densities. Plants growing at rocky ridges were affected by drought and salinity together. Those acquired the highest Na+ and Na+/K+, associated with the lowest in osmotic potential. In general, L. monopetalum able to exclude salt outside cells via salt glands scattered on leaf surfaces. These mechanisms permit L. monopetalum to tolerate and survive under stressful coastal habitats of Egypt.
... Previous studies have applied both direct and indirect approaches to quantify this parameter. However, they show that LAI is one of the most difficult parameters to measure and time consuming (Chen & Cihlar, 1995;Cutini, Matteucci, & Mugnozza, 1998;Schofield, 2016). ...
Three-dimensional characterisation of foliage and wood distribution within forests is essential for understanding, managing and monitoring forest ecosystems. The recent advances in terrestrial laser scanning (TLS) technologies have provided new opportunities to measure the 3D structure of forest canopies, which in turn can be correlated to tree attributes. In addition to estimation of variables such as stem density and the diameter at breast height and tree height, dual- and multi-wavelength systems are now being tested to distinguish foliage and wood based on their reflectance properties. Previous studies have suggested that using spectral information to distinguish foliage from wood materials is unlikely to provide an accurate classification on its own. In this thesis, a spectral approach was designed based on the frequency distribution of the reflectance and spectral ratios to distinguish between the foliage and woody materials. Additionally, a spatial classifier (CANUPO) approach was applied to describe the geometric relationships between the points of the TLS point clouds and characterise the local dimensionality at a given location and scale. TLS point cloud data of small broadleaf and needle-leaf trees in the laboratory, three single isolated oak trees with different structure and appearance and a full forest stand plot were used for foliage/wood classification in this research. The spectral and spatial classifications were compared to investigate the compatibility between them for all data sets. The results showed a clear separation of foliage and wood using 1063 nm and NDI data for the broadleaf tree and 1545 nm data for the needle-leaf tree. In contrast, the 1545 nm for the broadleaf and 1063 nm and NDI of the needle-leaf tree produced classification errors. A large number of foliage points were classified as wood for both trees using the spatial approach, with comparative errors of 67.35% and 73.18% for the broadleaf and needle-leaf tree respectively. For the three single trees, the 1545 nm data provide a clear separation for all trees while there was a variation in the classification using 1063 and NDI data for every tree. In general, the spatial classifier showed a clear separation for all of the trees with a few apparent errors in the canopy and on the stems with different results according to their structure and appearance. It was unlikely to be possible to separate foliage and wood using spectral data and ratios for the full forest data at ranges greater than 17m from the scanner. CANUPO classified 15% of the points as foliage and 85% as wood at a range of less than 15m. The classification showed a compatibility of 55.63% for the full stand data. Overall, the results highlight the potential of a dual-wavelength laser scanners for providing a wide range of data for forest ecology.
... To accomplish this in a single procedure, LAI-meters of LI-Cor are equipped with a fisheye lens. The sensor consists of five concentric silicon rings for light detection of the respective five concentric sky sectors (Cutini et al., 1998). The zenithal FOV adds up to 148° (s. Figure 2-1). ...
... In this publication, we were not able to collect ground truth measurements for the leaf areas. We will utilize the Li-Cor Leaf Area Meter (LI-COR Biosciences, Lincoln, NE, USA) or the CI-202 Laser Area Meter (CID Bio-Science, Inc., WA, USA) to collate the measurements of this Leaf Scanner device in the following tests (Cutini et al., 1998). ...
During recent years, portable plant phenotyping instruments have become increasingly important to monitor conditions of plant health non-destructively in the greenhouse and field environments. These devices, such as the Soil Plant Analysis Development (SPAD) meter, leverage indices that represent leaf chlorophyll content due to its strong correlation with leaf nitrogen (N) content. However, instruments such as SPAD meters are expensive and measure only individual, restricted leaf regions per data capture. In this publication, we developed a Leaf Scanner device to analyze the chlorophyll content distributions of whole leaves with greater efficiency and precision. The validating samples for this device were top-collared corn leaves grown under high and low N treatments in a greenhouse. For each region of a corn leaf, this device rapidly flashed visible and near infrared (NIR) LEDs to obtain the visible and NIR transmittance images of leaves. These images were summarized pixel-wisely into the Green NDVI index. A sufficient high framerate permitted continuous collection of regional index images. Using image registration techniques, these regional images were stitched together into a 'leaf panorama'. The total pixel amount of each leaf panorama, thus, served as a substitute for leaf area. A Minolta SPAD-502Plus meter collected ground-truth measurements along the length of each leaf sample. The results showed that there was a strong correlation between the average Leaf Scanner's measurements and averaged SPAD values (R 2 = 0.92), and the Leaf Scanner was able to clearly detect differences between high and low fertilized samples in terms of chlorophyll content and leaf area. Furthermore, this Leaf Scanner device enabled us to study the chlorophyll content distributions on the plants under different treatments.
Tree allometry is a plastic feature, and scaling parameters can vary considerably depending on phylogeny, life strategies, growth conditions and ontogeny. We hypothesized that in multi-layered forests growing on rich sites and driven by stand dynamics without stand-replacing disturbances, light is a primary driver of allometric relationships and that the morphological plasticity of tree species is closely associated with their shade tolerance. We quantified and compared the morphological properties of six species that form a shade tolerance gradient: Alnus glutinosa (L.) Gaertner, Quercus robur L., Fraxinus excelsior L., Ulmus laevis Pall., Tilia cordata Miller and Carpinus betulus L. The relationships between tree height and local stand density as predictors and dbh, crown width, crown length and crown volume as response variables were characterized. We found that in the lower stand layer the values of crown parameters increased with tree height at a lower rate in light-adapted than in shade-tolerant species. Conversely, the response of morphological traits on competition was stronger in light-adapted species than in shade-tolerant species. The ratio of crown width-to-crown length was not associated with light demand. Apart from ash, which demonstrated a different allocation pattern, between-species differences in the slenderness ratio were insignificant. Allometry and sensitivity to competition varied in trees growing in the upper and lower stand layers. Our results indicate that the dichotomy of basic growth strategies of stress tolerance versus stress avoidance is overly simplistic and fails to consider social status and species-specific features such as apical control.
The aim of the study was to compare a patch-mosaic pattern in the old-growth forest stands developed in various climate and soil conditions occurring in different regions of Poland. Based on the assumption, that the patch-mosaic pattern in the forest reflect the dynamic processes taking place in it, and that each type of forest ecosystem is characterized by a specific regime of natural disturbances, the following hypotheses were formulated: (i) the patches with a complex structure in stands composed of latesuccessional, shade-tolerant tree species are more common than those composed of early-successional, light-demanding ones, (ii) the patch-mosaic pattern is more heterogeneous in optimal forest site conditions than in extreme ones, (iii) in similar site conditions differentiation of the stand structure in distinguished patches is determined by the successional status of the tree species forming a given patch, (iv) the successional trends leading to changes of species composition foster diversification of the patch structure, (v) differentiation of the stand structure is negatively related to their local basal area, especially in patches with a high level of its accumulation. Among the best-preserved old-growth forest remaining under strict protection in the Polish national parks, nineteen research plots of around 10 ha each were selected. In each plot, a grid (50 × 50 m) of circular sample subplots (with radius 12,62 m) was established. In the sample subplots, species and diameter at breast height of living trees (dbh ≥ 7 cm) were determined. Subsequently, for each sample subplot, several numerical indices were calculated: local basal area (G), dbh structure differentiation index (STR), climax index (CL) and successional index (MS). Statistical tests of Kruskal- Wallis, Levene and Generalized Additive Models (GAM) were used to verify the hypotheses. All examined forests were characterized by a large diversity of stand structure. A particularly high frequency of highly differentiated patches (STR > 0,6) was recorded in the alder swamp forest. The patch mosaic in the examined plots was different – apart from the stands with a strongly pronounced mosaic character (especially subalpine spruce forests), there were also stands with high spatial homogeneity (mainly fir forests). The stand structure in the distinguished patches was generally poorly related to the other studied features. Consequently, all hypotheses were rejected. These results indicate a very complex, mixed pattern of forest natural dynamics regardless of site conditions. In beech forests and lowland multi-species deciduous forests, small-scale disturbances of the gap dynamics type dominate, which are overlapped with less frequent medium-scale disturbances. In more difficult site conditions, large-scale catastrophic disturbances, which occasionally appear in communities formed under the influence of gap dynamics (mainly spruce forests) or cohort dynamics (mainly pine forests), gain importance.
Canopy clumping index (CI) characterizes the spatial distribution of leaves or needles within a vegetation canopy. CI is critical in determining the canopy radiation transfer, photosynthesis, and hydrological processes. This paper reviews the field measurement and remote sensing estimation methods, characteristics, and applications of CI. CI is generally estimated in the field using direct, indirect optical, and allometric methods. The basis for the indirect optical approach is the gap-fraction based method. Remote sensing of CI is carried out using passive optical and active LiDAR technology. Current CI products are mainly derived from an empirical relationship with the normalized difference hotspot and darkspot (NDHD) index. Further CI product validation studies should be conducted using enhanced field measurements. CI typically shows vertical, scale, directional, and temporal variations. The overall CI is calculated as the integration of the directional CI values. CI is a key parameter in leaf area index (LAI) estimation, and canopy reflectance and land surface modeling studies. Future studies should focus on the adoption of automated and wireless measurement methods, development of new remote sensing estimation methods, improving our understanding of the CI characteristics, and accounting for CI in land surface models.
Der Blattflächenindex (engl.: leaf area index, LAI) ist ein wichtiger Bestandteil vieler Modelle für Biomasseproduktion und Wasserhaushalt sowie ein Indikator für Kronenzustand und Waldwachstum im forstlichen Umweltmonitoring. Zur Messung stehen verschiedene direkte und indirekte Methoden, mit jeweils unterschiedlichen Berechnungsverfahren und Korrekturfaktoren, zur Verfügung, deren Ergebnisse teils deutlich voneinander abweichen. Mittels digitaler hemisphärischer Fotographie (engl.: digital hemispherical photography, DHP), Licor LAI-2000 Plant Canopy Analyzer (PCA) und SunScan wurde in der vorliegenden Arbeit auf mehreren Versuchsflächen mit unterschiedlichen Baumarten der LAI ermittelt und die Ergebnisse sowohl untereinander als auch mit dem LAI des Streufalls vorhergehender Jahre hinsichtlich Plausibilität, Reproduzierbarkeit und Kosten verglichen.
Werden die Fotos und Messungen eines Messtermins mit unterschiedlichen Berechnungsverfahren ausgewertet, korrelieren die Ergebnisse signifikant. Im Vergleich dazu findet man aber eine bessere Übereinstimmung zwischen den Ergebnisse verschiedener Messtermine und Methoden, wenn bei deren Auswertung das gleiche Berechnungsverfahren zum Einsatz kommt. Eine wichtige Information, im Zusammenhang mit der Messung des LAI, ist die Verteilung der Blattwinkel. Künstliche Testbilder und Messungen des SunScan zeigen, dass Fehleinschätzungen des LAI die Folge sind, wenn die Verteilung in einem Berechnungsverfahren nicht berücksichtigt oder vom Benutzer nicht korrekt festgelegt wird. Mischbestände mit Buche und einer dichten Schattenkrone führen bei der LAI-Bestimmung mit DHP und PCA zu Problemen. Auf diesen Flächen stellt der SunScan eine interessante Alternative dar, da dieser auf einem anderen Messansatz basiert.
Die digitale hemisphärische Fotographie hat sich als flexible Methode erwiesen, da keine Referenzmessung im Freiland erforderlich ist und Korrekturfaktoren für die Klumpung berechnet werden können. Mit den Fotos werden permanente Aufzeichnungen geschaffen, die eine visuelle Überprüfung ermöglichen und mit zukünftigen Berechnungsverfahren erneut ausgewertet werden können. Zudem lässt der durchgeführte Kameravergleich den Rückschluss zu, dass eine günstige Fotoausrüstung keine Nachteile mit sich bringt.
Jedoch sind alle Methoden mit Fehlern behaftet, sodass der wahre Wert des LAI unbekannt bleibt. Verletzungen der Voraussetzungen der Berechnungsverfahren, Beeinflussung durch Benutzer und unterschiedliche Strahlungsbedingungen bei der Arbeit im Gelände sind vermutlich die Hauptursachen für Abweichungen in den Ergebnissen.
The free (unobstructed) sight through the foliage layer of forest canopy is expected to depend on the density of the foliage, i.e. dense foliage shortens the free sight while sparse one extends it. Conversely, it is possible to estimate foliage density from the free sight. Furthermore, it is possible to estimate from the free sight the amount of leaves in terms of leaf area or leaf area index (LAI) as a product of estimated foliage density and the thickness of the foliage layer. This paper presents a simple theory of estimating LAI from the free sight along with its verification using a set of field data from boreal forest of Canada. Free sight through the canopy was measured using airborne laser altimetry (ALA). Laser beams emitted vertically from an aircraft are reflected from different layers of the canopy, ranging from the uppermost canopy surface to the ground. The distance that a laser beam travels unimpeded into the canopy was assumed to be the free sight or more aptly, the free path, and the mean of a number of penetrations within the canopy as a good measure of the amount of leaf area. We assembled a set of field leaf area and mean free path data for 13 boreal forest sites in central Alberta, Canada. We related leaf area density with mean free path and found an inverse relationship between them. Furthermore, we verified that LAI can be estimated as a product of mean free path-based leaf area density and an estimate of canopy depth (D) obtained based on the relationships we found between D and mean tree height (H) and between H and mean laser vegetation height.
We quantified stand leaf area index and vertical leaf area distribution, and developed canopy extinction coefficients (k), in four mature hardwood stands. Leaf area index, calculated from litter fall and specific leaf area (cm2-g~'), ranged from 4.3 to 5.4 m2-m~2. In three of the four stands, leaf area was distributed in the upper canopy. In the other stand, leaf area was uniformly distributed throughout the canopy. Variation in vertical leaf area distribution was related to the size and density of upper and lower canopy trees. Light transmittance through the canopies followed the Beer-Lambert Law, and k values ranged from 0.53 to 0.67. Application of these k values to an independent set of five hardwood stands with validation data for light transmittance and litter-fall leaf area index yielded variable results. For example, at k = 0.53, calculated leaf area index was within ±10% of litter-fall estimates for three of the five sites, but from -35 to +85% different for two other sites. Averaged across all validation sites, litter-fall leaf area index and Beer-Lambert leaf area index predictions were in much closer agreement (±7 to +15%).
The vertical distribution of forest canopy elements is an important factor in canopy-atmosphere exchange processes and knowledge of the shape of the average vertical profile of leaf area density is a critical input to models of these processes. This study was conducted to determine the spatial variability of Leaf Area Index (LAI) in an oak forest when estimated with indirect fisheye techniques. A 35 mm camera with a 180° hemispherical lens and a LI-COR LAI-2000 Plant Canopy Analyzer (wavelengths < 490 nm) were used simultaneously to estimate vertical leaf area profiles and the horizontal variability in an oak forest in central Pennsylvania. Measurements were made at eight different heights in the canopy and repeated at nine different locations. The two sensors were in reasonable agreement. The photographic technique estimated the total leaf area index (LAI) to be 3.58, and the light sensor estimates resulted in an estimate of 3.40. The average precision was 8% for the LAI-2000 and 17% for the photographic technique. The point-to-point spatial variability of the LAI estimates was low when the whole canopy was measured from the ground and quite high when measuring the upper canopy. Ground level estimates of LAI using these fisheye techniques spatially average the canopy to the point where only four replications were necessary to sample the total LAI with 90% confidence. For. Sci 38(4):854-865.
We compared direct and indirect estimates of leaf area index (LAI) for lodgepole and loblolly pine stands. Indirect estimates
of LAI using radiative methods of the LI-COR LAI-2000 Plant Canopy Analyzer (PCA) did not correlate with allometric estimates
for lodgepole pine, and correlated only weakly with litter-trap estimates for loblolly pine. The PCA consistently under-estimated
LAI in lodgepole pine stands with high LAI, and over-estimated LAI in the loblolly pine stands with low LAI. We developed
a physical model to test the hypothesis that the PCA may under-estimate LAI in high leaf area stands because of increased
foliage overlap and, therefore, increased selfshading. Radiative estimates of LAI using the PCA for the physical model were
consistenly lower than allometric measures. Results from the physical model suggested that increased foliage overlap decreased
the ability of the PCA to accurately estimate LAI. The relationship between allometric and radiative measures suggested an
upper asymptote in LAI estimated using the PCA. The PCA may not accurately estimate LAI in stands of low or high leaf area
index, and the bias or error associated with these estimates probably depends on species and canopy structure. A species specific
correction factor will not necessarily correct bias in LAI estimates using the PCA.
Mature vegetation from 8 of the 12 major vegetation zones in Oregon and Washington was sampled along a transect from the Pacific Coast to the east slopes of the Cascade Mountains. Aboveground-overstory net primary production (NPP) ranged from <1 to 15 Mg ha-1 yr-1, aboveground biomass from 3 to 1500 Mg/ha, and area of all sides of leaves from 1 to 47 ha/ha; minima were in the shrub-steppe zone and maxima in the coastal forest zone. Maximum leaf area index, biomass and NPP were all strongly related both to a simple index of growing season water balance and to mean minimum air temperatures in January. In the subalpine conifer zone, though, cold winter temperatures have a stronger influence than summer water availability. Of the water balance components, evaporative demand alone could account for >90% of the variation in leaf area index. Although annual precipitation ranged from 20 cm in the shrub-steppe to 260 cm at the coast, it was a relatively poor predictor of stand structure and production. Biomass and NPP increased linearly up to a leaf area of c.30 ha/ha; above this point, biomass continued to increase while NPP decreased. Compared to other forested regions of the temperate zone with the same NPP, these systems receive more annual precipitation and average twice the basal area and biomass. -from Author
Projected leaf area index (LAI) and Beer-Lambert Law extinction coefficients (K) were estimated for 28-year-old Picea abies (L.) Karst., Larix decidua Mill., Pinus resinosa Ait., and Pinus strobus L. plantations using vertical profile data obtained with a portable integrating radiometer (sunfleck ceptometer). Predicted
LAI values were compared with direct measures of LAI. Based on dimensional analysis, LAI ranged from 5.0 for Larix decidua to 10.5 for Picea abies. Significant inverse relationships between cumulative LAI and canopy transmitted radiation were observed for the four species
(R2 = 0.92–0.97). Beer-Lambert extinction coefficients ranged from 0.39 for Picea abies to 0.84 for Pinus strobus
Stand-level predictions of LAI based on the Beer-Lambert Law were compared with measured LAI values for eight conifer and
six broadleaf stands. Using local K estimates resulted in predicted LAI values with an average 6% error. Using published K values resulted in an average error of 20%. High LAI and concomitantly low light levels below the canopy of Picea abies stands resulted in large overestimation errors in predicted LAI, rendering the sunfleck ceptometer inappropriate for forests
with large LAIs.
Leaf-area index (LAI, the projected total surface area of foliage per unit ground area) of an old-growth Douglas-fir stand in western Oregon was estimated from litterfall, light interception, sapwood cross-sectional area, and tree diameter. Estimates made by the first three techniques were similar, but the estimate based on tree diameter was twice as high as the others. For large trees with variable amounts of live crown, estimates of leaf area based on tree diameter appear to be inaccurate; therefore, the exceedingly high leaf-area indices previously reported for Douglas-fir forests are unreliable. Sapwood cross-sectional area varies in correspondence with the canopy area and therefore is a better estimator of leaf area on large trees. Maximum LAI estimates based on sapwood area are similar to those for other temperate coniferous forests.
1. In order to find a practical means of estimation of the production of matter in a plant community and to give a logical explanation to the variability of directly measured values, theoretical analyses have been advanced of the interrelationshipsbetween leaf amount, light distribution and total foliage photosynthesis2. Inside foliage relative light intensity received by the leaves is not always the same as the light intensity measured at horizontal plane at the same height (Fig. 1). In homogeneous stands the former can be derived from Equation (3), when leaf transmissibility is known and extinction coefficient (K in Equation (2)) is obtained beforehand by 'stratifying clip method'.3. If photosynthetic capacity in the active leaf and mean respiration rate of all the leaves in a stand are known, the mean total daily photosynthesis of whole foliage is estimated by Equation (5). An example in representative herbaceous species is presented in Fig. 5, where it is clearly indicated that with lower 'leaf area index' daily production in foliage is indifferent to inclination of leaves, while with increase of leaf amount the role of inclination in the production becomes very remarkable, upright leaves being more efficient than horizontal ones under full daylight as demonstrated by Watson and Witts.4. Compensation light intensity and 'optimum leaf-area index' (Fopt-leaf amount February 1960 SAEKI, T. 63 in the form of LAI for the highest production) are calculated from the photosynthetic capacity in the active leaf and respiration rate of the lower leaf (Equations (6) and (7)). The obtained values seem to be quite reasonable in consideration of the minimum light intensities and 'leaf area indexes' in the natural communities.5. The highest daily production in a plant community, Pmax, calculated with Equation (8) was discussed in relation to the extinction coefficient and incoming radiation (Figs. 7 and 8). An approximate coincidence was recognized between the calculated values and the highest net production in crop fields collated by Blackman and Black.The author should like to express his sincere thanks to Prof. M. Monsi for his
Canopy transmittance was measured at 1200 and 1400 local solar time using an integrating radiometer on seven coniferous forest stands in western Montana, ranging in projected leaf area index (LAI) from 1.7-5.3 m^2/m^2. Transmittance of each 1-ha stand was measured at 96,000 points, yet measurement required <1 h because the instrument instantaneously integrates 80 radiometer measurements at once. The Beer-Lambert Law was inverted to estimate LAI using measured transmittance and an extinction coefficient of 0.52. LAI estimated by transmittance was highly correlated with LAI measured by sapwood-based allometric equations at both the 1200 (R^2 = 0.97) and 1400 (R^2 = 0.94) measurement times. The results suggest that the technique has a wide applicability given the range of LAIs, stand densities (450-4140 trees/ha) and illumination angles (32@?-57@?) under which it was tested.
For the purposes of this discussion, temperate forest is regarded as occurring in broad latitudinal bands between the taiga towards the poles and the mediterranean flora towards the equator. Within these bands temperate forest occurs at moderate elevations below the altitudinal extremes of climate and associated alpine vegetation and away from the continental extremes of temperature and dryness. Temperatures are moderate, usually not falling below about -15 °C in winter, and the soil freezes for less than 3 months. In summer temperatures rarely exceed 35 °C, precipitation exceeds ca. 400 mm and is fairly uniformly distributed through the year so that a dry season lasts for less than ca. 3 months. A more exact definition can be found in Walter (1970).
This chapter demonstrates two structural properties of plant communities—canopy leaf area and growth efficiency. It develops four basic premises that (1) canopy leaf area can be related to competition for light, (2) growth efficiency is responsive to canopy leaf area and other identified environmental factors, (3) potential productivity or site capability can be estimated from knowing maximum canopy leaf area, and (4) canopy leaf areas for trees or stands can be nondestructively estimated by determining sapwood cross-sectional area at a convenient reference height. Canopy leaf area and its vertical distribution can be accurately estimated through correlations with conducting sapwood area throughout the crown. Species within the same genera have widely differing ratios of leaf area to sapwood area. To estimate the canopy leaf area on large trees, the linear taper in sapwood area from breast height (1.37 m) to the base of the crown must be determined.
ABSTRACT Running, S.W. and Coughlan, J.C., 1988. A general model of forest ecosystem processes for regional applications. I. Hydrologic balance, canopy gas exchange and primary production processes. Ecol. Modelling, 42: 125-154. An ecosystem process model is described that calculates the carbon, water and nitrogen
In stands of Salix viminalis growing near Edinburgh accumulated dry matter was linearly related to accumulated intercepted radiation until heavy leaf fall. The slopes of the relationships for above-ground dry matter were 0.99 g MJ-1 in 1984 and 1.38 g MJ-1 in 1985. This difference in light-use efficiency (rather than a difference in amounts of light intercepted) was primarily responsible for a difference between years in above-ground dry matter production (11 t ha-1y-1 in 1984 and 14 t ha-1y-1 in 1985). Greater efficiency in 1985 was attributed to better water and nutrient supplies and lower levels of incoming radiation. Leaf area index reached 2.4 in 1984 and 4.5 in 1985. Stems alone intercepted 60% of total solar radiation after leaf fall in 1984 and 47% in 1985 when the 'stem area index' reached 1.5. Leaf-area development in spring was a function of thermal time, with an earlier starting time for the coppiced stand in 1984, resulting in c20% greater potential light interception (1240 MJ m-2 y-1). -from Authors
Because leaf area index (projected one-sided leaf surface area per unit ground surface area, hereafter referred to as LAI) is a critical variable in models that attempt to simulate carbon, nutrient, water, and energy fluxes for forest ecosystems (e.g., Running and Coughlan 1988), techniques to rapidly estimate LAI over large areas are in great demand. LAI can be measured either directly or indirectly (e.g., Norman and Campbell 1989). Direct techniques involve dimensional analysis of the canopy and imply felling trees that are representative of the stands being studied. As a consequence, these techniques are labor-intensive and expensive. Moreover, the allometric relations are influenced by environmental factors and therefore may not
The canopies of northern hardwood forests dominated by sugar maple (Acer saccharum Marsh.) were examined at five locations spanning 800 km along an add deposition and climatic gradient in the Great Lakes region. Leaf area index (LAI) calculated from litterfall ranged from 6.0 to 8.0 in 1988, from 4.9 to 7.9 in 1989, and from 5.3 to 7.8 in 1990. The data suggest that maximum LAI for the sites is between 7 and 8. Insect defoliation and the allocation of assimilates to reproductive parts in large seed years reduced LAI by up to 34%. Allometric equations for leaf area and foliar biomass were not significantly different among sites. They predicted higher LAI values than were estimated from litterfall and could not account for the influences of defoliation and seed production. Canopy transmittance was a viable alternative for estimating LAI. Extinction coeffidents (K) of 0.49 to 0.65 were appropriate for solar elevations of 63° to 41°. Patterns of specific leaf area (SLA) were similar for the sites. Average sugar maple SLA increased from 147 cm² g-1 in the upper 5 m of the canopy to 389 cm² g-1 in the seedling layer. Litterfall SLA averaged 196 cm² g-1 for all spedes and 192 cm² g-1 for sugar maple. Similarity among the sites in allometric relationships, maximum LAI, canopy transmittance, and patterns of SLA suggests these characteristics were controlled primarily by the similar nutrient and moisture availability at the sites. A general increasing trend in litter production along the gradient could not be attributed to N deposition or length of growing season due to year to year variability resulting from insect defoliation and seed production. For. Sci. 37(4):1041-1059.
We compared estimates of leaf area index (LAI) based on tree allometrics and light interception in 15 lodgepole pine (Pinus contorta var. latifolia) stands in southeastern Wyoming. LAI from stem allometrics was estimated with a local equation demonstrated to produce accurate and unbiased leaf area estimates for the stand conditions in this study. LAI from measured light interception, estimated with a species-average light extinction coefficient using the Beer-Lambert Law, was not correlated with LAI determined from tree allometrics. Light extinction coefficients varied from 0.29 to 0.67 when determined from allometric estimates of LAI and measured light interception. The derived light extinction coefficients were inversely correlated with LAI (r² = 0.79). High LAI may be associated with canopy architectures where foliage distribution results in reduced light capture effectiveness. Variation in light capture by lodgepole pine canopies may preclude the use of a species average light extinction coefficient for estimating LAI. For. Sci. 37(6):1682-1688.
This study evaluated one semi-direct and three indirect methods for estimating leaf area index (LAI) by comparing these estimates with direct estimates derived from litter collection. The semi-direct method uses a thin metallic needle to count a number of contacts across fresh litter layers. One indirect method is based on the penetration of diffuse global radiation measured over the course of a day. The second indirect method uses the LAI-2000 plant canopy analyser (PCA) which measures diffuse light penetration from five different sky sectors simultaneously. The third indirect method uses the Demon portable light sensor to measure the penetration of direct beam sunlight at different zenith angles over the course of half a day. The Poisson model of gap frequency was applied to estimate plant area index (PAI) from observed transmittances using the second and third methods. Litter collection from 11 temperate decidous forests gave values of LAI ranging from 1.7 to 7.5. Estimates based on the needle method showed a significant linear relationship with LAI values obtained from litter collections but were systematically lower (by 6–37%). PAI estimates using all three indirect techniques (fixed light sensor system, LAI-2000 and Demon) showed a strong linear relationship with LAI derived from litter collection. Differences, averaged over all forest stands, between PAI estimates from each of the three indirect methods and LAI from litter collections were below 2%. If we consider that LAI=PAI–WAI (wood area index) then, all three indirect methods underestimated LAI by an additional factor close to the value of WAI. One reason could be a local clumping of architectural canopy components: in particular, the spatial dispositions of branchlets and leaves are not independent, leading to a non-random relationship between the distributions of these two canopy components.
Radiation transmission through plant canopies is shown to be determined not only by the geometry of the foliage elements (leaves), but also by the geometry of foliage clumps. When the geometry of tree branches (thin slabs of foliage in which leaves are confined) was considered with a Poisson model, it was found that beam transmission measurements at a 62° rather than a 57.5° incident angle can provide a good estimate of the effective leaf area index (Le). The values of Le calculated from the model were approximately 55–65% of the actual leaf area index when the branches were assumed to consist of one layer of randomly dispersed leaves. The calculated results are consistent with experimental data obtained from a Douglas-fir forest stand, which was largely composed of near-horizontal branches.
We estimated leaf area index (LAI) in a needle-leaved forest and a broad-leaved orchard using four instruments which measure fractional light penetration through the canopy. Gap fraction data were analyzed by a one-dimensional inversion model or by using the Beer-Lambert Law. Instrument and analytical technique both had a strong influence on calculated LAI. There was no consistent pattern of LAI results among instruments so no simple cross-calibration can be offered. Three of the four instruments accurately estimated orchard LAI when used with one or the other analytical technique. In addition to performance, practical considerations including cost, sampling, and data analysis were also compared among the instruments. Because the instruments do not provide consistently accurate LAI estimates, LAI should be independently corroborated before use in any particular situation. These instruments may be most useful for relative LAI comparisons in a specific canopy type when a single combination of instrument and analytical technique is employed.
Hemispherical photographs were taken beneath an 80-years-old Douglas-fir (Pseudotsuga menzie sii) forest stand under clear and overeast sky conditions, and under clear sky with the canopy partially covered with snow. The photographs were digitized using an optical scanner. The ‘effective plant area index’ () and the distribution of the inclination angle of plant elements were obtained with Norman and Campbell's linear least-square inversion technique. Photographic exposure was determined by matching the values obtained from the photographs with those measured using the Plant Canopy Analyzer (PCA) (Li-Cor LAI-2000). Agreement between the inverted and measured values was found when the photographs were underexposed by 4–5 stops compared with readings of a light meter facing vertically upward under the canopy. These values of were about half the plant area index calculated from the measurements of tree diameter at breast height () using published relationships for Douglas-fir trees. The distribution of sky radiance under clear and overcast conditions had a considerable effect on the determination of the angular distribution of plant elements. Pronounced differences were found between inclination angle distributions calculated from the PCA gap fraction measurements and the digitized photographs taken with and without a blue filter (Wratten 80B). These differences may have resulted from the effect of the scattering and possibly diffraction of the visible radiation by the foliage. The scattering and diffraction caused more leaves to blend into the sky at small than at large zenith angles.
An array model, MAESTRO, was developed to predict radiation absorption, photosynthesis and transpiration by the individual crowns of trees in a stand and by the stand as a whole. The fluxes of radiation are treated in the photosynthetic (PAR), near infrared (NIR) and thermal wavebands; beam and diffuse radiation are considered separately. The spatial heterogeneity of the leaf area density distribution within the tree crown has been incorporated into MAESTRO, which can be used to study the spatial distribution of the radiation regime, and of the water vapour and carbon dioxide exchanges of leaves within the tree crown, in relation to stand structure. This model has been tested by comparing the calculated hourly and daily fluxes of PAR with measurements made by quantum sensors at locations below the tree crowns using three different submodels of leaf area density distribution. Good agreement between measurements and predictions was obtained.
An ecosystem process model is described that calculates the carbon, water and nitrogen cycles through a forest ecosystem. The model, FOREST-BGC, treats canopy interception and evaporation, transpiration, photosynthesis, growth and maintenance respiration, carbon allocation above and below-ground, litterfall, decomposition and nitrogen mineralization. The model uses leaf area index (lai) to quantify the forest structure important for energy and mass exchange, and this represents a key simplification for regional scale applications. FOREST-BGC requires daily incoming short-wave radiation, air temperature, dew point, and precipitation as driving variables. The model was used to simulate the annual hydrologic balance and net primary production of a hypothetical forest stand in seven contrasting environments across North America for the year 1984. Hydrologic partitioning ranged from 14/86/0% for evaporation, transpiration and outflow, respectively, in Fairbanks, AK (annual precipitation of 313 mm) to 10/27/66% in Jacksonville, FL (annual ppt of 1244 mm), and these balances changed as lai was increased from 3 to 9 in successive simulations. Net primary production (npp) ranged from 0.0 t C ha−1 year−1 at Tucson, AZ, to 14.1 t C ha−1 year−1 at Knoxville, TN and corresponded reasonably with observed values at each site. The sensitivity of ecosystem processes to varying lai in different climates was substantial, and underscores the utility of parameterizing this model at regional scales in the future with forest lai measurements derived from satellite imagery.
Two indirect gap fraction methods for estimating leaf area index (LAI) are compared with estimates from litterfall collections in a mixed-age oak-hickory forest. One indirect method uses averaged, direct beam penetration data obtained with a moving tram. The second uses a portable light sensor system that measures diffuse light penetration for five sky sectors between zenith angles 0 and 75°. Data were collected from September 1989 to January 1990.The Poisson model and the negative binomial model of gap frequency were applied to estimate LAI from observed transmittances. With the Poisson model, an assumption of a random leaf spatial distribution contributes to an underestimation of LAI by as much as 45%; this is because leaves at this site are actually clumped at both large and small scales. The negative binomial, which requires determination of a clumping parameter, produces estimates comparable with those of the litterfall method.Both indirect techniques accurately describe temporal changes in leaf area using either the Poisson or negative binomial model. The portable system also allows easy estimation of the spatial variation in leaf area within the site or between sites, and it can be used to obtain a vertical profile of leaf area.
- A Cutini
A. Cutini et al.r Forest Ecology and Management 105 1998 55–65
LAI-2000 Plant Canopy Analyzer Operating Manual
- Li-Cor
Li-Cor, 1991. LAI-2000 Plant Canopy Analyzer Operating Manual. Lincoln, NE, USA.
Recherches sur l'ecosysteeme foret. Serié`´ Serié Serié` Serié`´ B : La chenaie melangee calcicole de Virelles-Blaimont
- J P Vansereven
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On the light transmission of leaves and its meaning for the production of matter in plant communities
- Kasanga
Recherches sur l'écosysteème foret. Série B: La chenaie mélangée calcicole de Virelles-Blaimont. Contribution n. 30: L'index foliaire et sa measure par photoplanimétrie
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Physiology of woody plants
- P J Kramer
- T T Kozlowsky