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Relationship between forest density and albedo in the boreal zone
Ecological Modelling 261–262 (2013) 74–79
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Relationship between forest density and albedo in the boreal zone Petr Lukeˇs ∗ , Pauline Stenberg, Miina Rautiainen Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland
a r t i c l e
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Article history: Received 28 January 2013 Received in revised form 12 April 2013 Accepted 14 April 2013 Available online 16 May 2013 Keywords: Radiative transfer Forest reflectance model Boreal forest Albedo Biomass
a b s t r a c t The relationship between albedo and forest areas is complex. Little is known about the driving factors of albedo in the boreal zone. Using a radiative transfer model and an extensive forest inventory database, we simulated albedo of forest stands composed of the most abundant tree species of Fennoscandia – Scots pine, Norway spruce and Silver birch. The physically-based radiative transfer model allowed us to uncouple the driving factors of the forest albedo. We analyzed separately how biomass, canopy cover, and species composition influence the shortwave albedo of a boreal forest. The albedos differed significantly between species and increased with solar zenith angle. The lowest values were observed for spruce stands, followed by pine stands and the highest values were observed for birch stands. Diurnal courses of albedo were tightly related to forest density as quantified by biomass or canopy cover. The albedos generally decreased with increasing stand biomass and canopy cover whereas the sensitivity to solar angle increased as the stands became denser. The sharpest decrease in albedo was observed at low biomass values, after which the albedo remained relative stable. The strength of the relationships was weaker for larger solar zenith angles. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Changes in the amount of forest cover and biomass can have diverse effects on global climate and carbon sequestration via various feedback mechanisms, such as fluctuations in the land surface albedo and effects on the global water cycle. On the other hand, changes in climate directly affect the functioning of forests via the frequency of occurrences of natural disturbances, CO2 fertilization, and alterations in the length of the growing season (Betts et al., 2007). Among terrestrial biomes boreal forests have the greatest effect on annual mean global temperature (Snyder et al., 2004). The on-going increase in boreal forest biomass in Europe and parts of Asian Russia can influence the global climate not only through carbon fixation but also through altering the albedo. However, the link between forest land and its albedo is complex: very little is known about the influence of natural disturbances and human activities (such as forest management procedures) on albedo. Albedo perturbations due to natural forest disturbances can either enhance or reduce the positive radiative forcing from CO2 efflux (O’Halloran et al., 2012; Bernier et al., 2011). In regions seasonally covered by snow such as the boreal zone, removal of forest canopy will lead to an increase in albedo in winter; snow
∗ Corresponding author. Tel.: +358 09 191 58189. E-mail addresses: petr.lukes@helsinki.fi, [email protected] (P. Lukeˇs). 0304-3800/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecolmodel.2013.04.009
covered forest floors significantly affect the total canopy albedo (Manninen and Stenberg, 2009). Furthermore, the effects of stand age and development stage on albedo need to be considered (Bonan, 2008). In managed boreal forests, forestry practices affect the albedo not only through changes in biomass and canopy cover but also by altering the stand structure (Rautiainen et al., 2011a). A similar canopy cover or biomass can result from a range of forest structures, which cause different albedos. Whereas the general difference in the albedo of coniferous and deciduous forests has been long established (e.g. Betts and Ball, 1997), the reasons behind this are still partly unknown. Moreover, as there are indications that the currently conifer-dominated boreal forests are gradually shifting towards including more deciduous tree species, it is ever more important to understand the role of species composition on forest albedo. As the global forest area and biomass change independently (Rautiainen et al., 2011b), their effects on forest albedo need to be analyzed separately. Neither local albedo measurements nor satellite-based albedo products can explain the causality between small-scale environmental management scenarios and changes in albedo. Thus, forest reflectance models validated with satellite remote sensing data is the only possible method for linking quantitative changes in vegetation structure to albedo for large geographical regions. Forest reflectance models are parameterized using mathematical descriptions of canopy structure (e.g. leaf area index, tree height, crown dimensions, stand density), optical properties of leaves and forest floor, and spectral and angular properties of incoming radiation.
P. Lukeˇs et al. / Ecological Modelling 261–262 (2013) 74–79 Table 1 Tree species composition and understory types for the study sites Puumala, Saarinen and Hyytiälä.
Number of stands Dominant species (%) Pine Spruce Birch Understory type (%) Mesic Herb-rich Xeric
Puumala
Saarinen
361
326
Hyytiälä 8
67 26 7
28 53 19
4 43 53
89 0 11
96 3 1
50 38 12
Using these models, the spectral and broadband albedos of a forest can be calculated from more readily measurable variables such as forest structure and leaf optical properties. Here, we investigate the influence of forest biomass, canopy cover and species composition on the shortwave albedo of boreal forests using a forest reflectance model which uses routine forest inventory variables as input. We use an extensive forest inventory database collected in Finland covering the natural variation in stand structures. 2. Materials and methods 2.1. Study stands We simulated the albedo for 695 boreal forest stands located in three sites in Central and Eastern Finland, named Puumala, Saarinen and Hyytiälä. The stands represent the typical range in stand structures, development classes and site fertility types of managed boreal forests in Finland, and are dominated by the most abundant tree species in Northern Europe i.e. Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst) and birches (Betula pendula Roth or Betula pubescens Ehrh.) (Table 1). The forest inventory database available as input for the albedo simulations included leaf area index (LAI) and species-specific values of stand density (N), and medians of diameter at breast height (DBH), tree height (H) and crown length (LCROWN ). The understory type was assigned to each forest stand based on its site fertility class. The stands and measurements are described in more detail by Stenberg et al. (2004) and Korhonen et al. (2011). The two inputs for albedo simulations which were not directly measured were the crown radius (CR ) and total aboveground biomass. CR was calculated using an allometric relationship between DBH and CR developed by Jakobsons (1970) for pine, spruce and birch of northern Sweden (latitudes > 60◦ ). Total aboveground biomass of simulated stands was estimated using the recently developed Finnish national multivariate models for birch (Repola, 2008), pine and spruce (Repola, 2009). Basic structural parameters of all forest stands (N = 695) are given in Table 2, and the structural parameters of monospecific stands (N = 291) in Table 3. The optical properties (directional-hemispherical reflectance and transmittance factors) of needles and leaves for the three species were obtained from a spectral database measured by Lukeˇs et al. (2013) in boreal Finland (Fig. 1a). For the two coniferous species, the shoot was chosen as the basic scattering element (Nilson and Ross, 1996), i.e. we used shoot spectra (instead of needle spectra) as input in the albedo simulations. Species-specific shoot spectra were obtained from needle spectra according to a previously published methodology (Rautiainen et al., 2012; Smolander and Stenberg, 2003) using average values of the shoot to total needle area ratio, STAR (Oker-Blom and Smolander, 1988). The STAR values used were 0.147 for pine (Smolander et al., 1994) and 0.161 for spruce (Stenberg et al., 1995).
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Optical properties of the forest understory were based on a database collected in Finland (Rautiainen et al., 2011c) covering typical forest understory types from herb-rich green understories to xeric lichen types (Fig. 1b). For each study stand, we assigned an understory spectrum (xeric, mesic or herb-rich) according to its site fertility class. Also bark and trunk optical properties were based on a previously published database (Lang et al., 2001). 2.2. Albedo simulations Albedo simulations for different solar zenith angles (SZA) were performed using the recently modified version (Mõttus et al., 2007) of the Forest Reflectance and Transmittance Model (FRT) (Kuusk and Nilson, 2000). FRT is a hybrid type of radiative transfer model, i.e. it includes properties of both geometric-optical and radiative transfer equation based models. The forward simulations of albedo for a large number of stands with a complex structure are relatively fast with the FRT because the model is computationally efficient and its parameterization is based on standard forest inventory data. More importantly, it is able to accurately simulate the spectral fluxes of a forest (Widlowski et al., 2007). Several tree classes with different structure, density and optical properties of foliage can be defined in FRT in order to simulate mixed stands. We simulated either one, two or three tree classes depending on the species composition of the study stand. Tree crowns were simulated with ellipsoid crowns which have been found to represent well crown shape and volume in our study species (Rautiainen et al., 2008; Mõttus et al., 2006). As described previously, the input parameters by species were obtained directly from the inventory database or derived using allometric equations (Table 4). The optical properties of leaves, shoots and bark were parameterized according to measured values (see Section 2.2) (i.e. one average spectrum of foliage and bark for each tree species). The forest floor was considered a Lambertian surface with a mesic, herb-rich or xeric type spectrum. In this study, we simulated the black-sky albedo, also known as directional-hemispherical albedo which has been specified as the product required for climate change purposes (GCOS, 2004). Forest albedo was simulated for two extreme solar zenith angles (40◦ and 70◦ ) during midsummer at latitudes corresponding to the study sites (around 61◦ ). In addition, the hourly diurnal course of albedo during summer solstice (DOY = 172) was simulated for hourly solar zenith angles between 6 am and 6 pm of apparent solar time. The albedo simulations were run at a 5 nm spectral resolution from 400 nm to 2400 nm. A 12 × 12 quadrature was used to integrate over all the viewing zenith and azimuth angles in the hemisphere. The broadband shortwave albedo was approximated as a sum of spectral albedos weighted by the incoming solar irradiances at the corresponding wavelengths. We used solar irradiance measurements which are recommended as the reference exo-atmospheric solar irradiance spectrum by the Committee on Earth Observation Satellites (CEOS) (Thuillier et al., 2003). Although our simulated spectral range (400–2400 nm) is somewhat narrower than the theoretical definitions of total shortwave broadband albedo (300–4000 nm), it covers the bulk part (ca. 98%) of the solar irradiance and thus gives a good approximation of total broadband albedo. 3. Results 3.1. The influence of species composition on albedo First, we focused on monospecific forest stands, i.e. stands with a 100% composition of pine, spruce or birch. From the original 695
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Table 2 Basic structural characteristics of the study stands (n = 695). Mean values and standard deviations (in parentheses) shown.
Stand density (trees/ha) DBH (cm) H (m) Lcrown (m) CR (m) Total aboveground biomass (kg/tree)
Pine
Spruce
Birch
891 (675) 14.60 (4.70) 12.10 (3.20) 6.53 (1.87) 1.27 (0.28) 80.00 (68.57)
686 (788) 16.60 (6.44) 13.80 (4.56) 8.77 (3.42) 1.44 (0.31) 115.64 (100.1)
491 (661) 11.32 (5.35) 10.33 (4.03) 6.47 (2.62) 1.40 (0.37) 46.46 (63.27)
Table 3 Basic structural characteristics of monospecific stands (n = 291). Mean values and standard deviations (in parentheses) shown.
Stand density (trees/ha) DBH (cm) H (m) Lcrown (m) CR (m) Total aboveground biomass (kg/tree)
Pine
Spruce
Birch
1084 (642) 13.77 (3.83) 11.15 (2.88) 5.93 (1.51) 1.22 (0.23) 59.84 (40.23)
806 (1076) 19.40 (6.46) 15.75 (4.15) 10.90 (3.26) 1.60 (0.31) 167.01 (105.6)
1167 (1124) 7.29 (3.46) 7.06 (3.90) 4.03 (1.97) 1.12 (0.24) 14.80 (17.69)
Fig. 1. The average single scattering albedo of pine and spruce needles and birch leaves (a) and the average hemispherical-directional reflectance factor (HDRF) of forest understory of mesic, herb-rich and xeric type (b).
stands there were 179 pure pine, 97 pure spruce and 15 pure birch stands. The mid-day albedos (SZA = 40◦ ) of monospecific forest stands differed significantly between species (Fig. 2). The lowest values were observed for spruce (average albedo of 0.11 with standard deviation of 0.03), and the highest for birch (0.22 ± 0.01). The simulated albedos of pine stands (0.14 ± 0.02) were between spruce and birch stands. We studied the impact of species composition on the albedo of mixed stands composed of spruce with either birch or pine as admixtures. We analyzed two cases: (a) the fraction of birch and (b) the fraction of pine in a spruce forest (Fig. 3). The fraction was expressed as the ratio of the number of birch (or pine) trees per hectare to the total number of trees per hectare. The average albedo
of mixed spruce-birch stands increased from 0.1 to 0.18 when the fraction of birch increased from 20% to 90%. A slight increase in albedo also occurred in the mixed spruce-pine stands with increasing fraction of pine, but the relationship was not as tight as for birch. 3.2. Diurnal variation in albedo The diurnal variation in albedo was analyzed using monospecific stands. The albedos simulated for the day of summer solstice stayed relatively constant from 9 am to 4 pm (SZA between 39◦ and 57◦ ) but clearly increased towards morning and evening hours (SZA larger than 57◦ ) (Fig. 4). The diurnal variation in albedo
Table 4 Additional parameters required by the FRT model. Pine
Spruce
Birch
References
Specific leaf weight (g/m )
161
202
57
Branch to total leaf area ratio
0.18
0.18
0.15
Tree distribution parameter Shoot length (cm) Shoot shading coefficient
10 0.59
1.2 5 0.64
Pine: Palmroth and Hari (2001), spruce: Stenberg et al. (1999), birch: Kull and Niinemets (1993) Pine: Stenberg et al. (2003), spruce and birch according to Nilson (1999) Nilson (1999)
40 1
2
Calculated as 4 × STAR for pine and spruce Smolander et al. (1994) and Stenberg et al. (1995)
P. Lukeˇs et al. / Ecological Modelling 261–262 (2013) 74–79
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50 Pine Spruce Birch
45
Number of stands
40 35 30 25 20 15 10
0.24
0.23
0.22
0.2
0.21
0.19
0.18
0.17
0.16
0.15
0.14
0.13
0.12
0.1
0.11
0.09
0
0.08
5
DHR Fig. 2. Albedo of monospecific pine, spruce and birch stands simulated by the FRT model.
was characterized by the ratio of morning to midday values) and increased with canopy cover (r = 0.86–0.89) for all species (Fig. 5). 3.3. The influence of biomass, leaf area index and canopy cover on albedo A decrease in albedo at SZA = 40◦ with increasing stand biomass, LAI, and canopy cover was observed for all species (Fig. 6). The relationship between albedo and these measures of forest density were similar with each other but the tightest for LAI. The sharpest decrease in albedo with increasing forest density was observed for sparse canopies. For denser canopies the albedo values remained relatively stable. Pine stands were separated into two groups based on their understory type: mesic and xeric. Stands with mesic understory had a similar relationship between forest density and albedo as spruce. For pine stands with xeric understory, on the other hand, the dependency was non-existent. The relationships
Fig. 4. Hourly average albedo and its standard deviation (vertical bars) for the monospecific pine, spruce and birch stands.
became weaker for large solar zenith angles and were almost flat at SZA = 70◦ (results not shown). 4. Discussion The boreal forests in Fennoscandia are typically composed of evergreen coniferous species (Scots pine and Norway spruce) with small proportions of deciduous birch. For example, the forests of Finland are composed of 65% pine, 24% spruce and 11% broadleaved species, mainly birch (Metla, 2011). Our extensive simulations of boreal forest albedo confirmed the observation from many previous studies (e.g. Betts and Ball, 1997) that there is a clear difference in albedo between different tree species, 1.4 1.3
Albedo ratio
1.2 1.1 1 0.9 0.8 0.7
Birch Coniferous
r=0.89 r=0.86
0.6 0
0.2
0.4
0.6
0.8
1
Canopy cover Fig. 3. The influence of fraction of birch or pine in mixed spruce-birch and sprucepine on the albedo of spruce stands.
Fig. 5. The relationship between canopy cover and albedo ratio for monospecific coniferous (pine and spruce combined) and birch stands. The albedo ratio is defined as forest albedo at SZA = 70◦ divided by forest albedo at SZA = 40◦ .
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Fig. 6. The relationship between albedo (at SZA = 40◦ ) and total aboveground biomass (a), LAI (b) and canopy cover (c) for monospecific pine, spruce and birch stands. Pine stands have been separated into two classes, mesic and xeric, based on their understory type.
especially between broadleaved species and spruce (Fig. 2). The clear differences in the albedos of monospecific spruce, pine and birch stands show that the composition and abundance of different species in mixed stands will significantly affect their albedo. The albedo of mixed spruce-birch stands doubled when the fraction of birch increased from marginal to dominant (Fig. 3). The fraction of pine, on the other hand, had a very small effect on the albedo of mixed spruce-pine stands. The lower albedo of coniferous species has been attributed to their hierarchical clumped structure which causes photons to be trapped within shoots and crowns (Rautiainen and Stenberg, 2005), as well as to the typically low single scattering albedo of needles (Roberts et al., 2004; Lukeˇs et al., 2013). Of the two coniferous species, spruce stands had the lower albedo, which in part may be explained by typically higher values of foliage biomass (and LAI) and canopy cover. During most of the day (SZA = 39◦ –57◦ ), the mean albedos remained rather stable (Fig. 4). They increased only in early morning or late evening, i.e. at large solar zenith angles. At these angles, however, the incoming levels of solar irradiance are very low. Thus, when calculating temporal courses of albedos, the mid-day values will have the largest weight. It should be observed, however, that the sensitivity to solar zenith angle, and thus temporal variation, in albedo increases with forest density (Fig. 5). The albedo was tightly related to measures of forest density (Fig. 6). However, for similar values of biomass, LAI and canopy cover, there were still distinctive differences between the albedos of the pine and spruce stands. This can be hypothesized to result from the lower needle single scattering albedo of spruce than of pine (Fig. 1) and the longer crowns of spruce canopies (Table 2). Although the albedos of monospecific stands generally decreased with forest density, their sensitivity to SZA increased (Fig. 5). We may, therefore, expect stronger diurnal fluctuations in albedo for dense stands with more closed canopies and higher biomass values. In boreal forests of Fennoscandia, 50% of the stands have a canopy cover lower than 0.5 (DeFries et al., 1995). This also turned out to be the most sensitive region for albedo changes (Fig. 6), arguably due to the significant role of forest understory. The understory type is closely linked to the fertility, species composition and geographic location of the stands. While the typical understory layers in the southern boreal region in, for example, Fennoscandia belong to mesic and herb-rich types, the lichen dominated xeric
type is common for the northernmost boreal forests dominated by pine. In general, the less fertile understory site types decrease the forest albedo, and the effect is larger the more open is the stand. The influence of understory on stand albedo was evident at small solar zenith angles and low biomass values (Fig. 6). 5. Conclusions Forest management practices, such as logging patterns or growing monospecific or mixed forests may have a significant influence on the albedo of the boreal biome. However, the influence of the resulting forest structure and species composition on the albedo of these forests has not been studied before using an extensive forest inventory database. In this study, we identified factors driving boreal forest albedo using a theoretical model. We show that species-specific stand albedos and their diurnal courses are tightly linked to forest density. The albedos differed significantly between species with the lowest values being observed for spruce and the highest for birch. From the forest management perspective, our results suggest that an increase in albedo can be achieved by (1) increasing the proportion of birch in conifer-dominated forests and (2) managing forests to have a low stand density throughout the rotation period. Acknowledgements The study was funded by the Academy of Finland. We thank Dr. Matti Mõttus and Dr. Janne Heiskanen for fruitful discussions. References Bernier, P.Y., Desjardins, R.L., Karimi-Zindashty, Y., Worth, D., Beaudoin, A., Luo, Y., Wang, S., 2011. Boreal lichen woodlands: a possible negative feedback to climate change in eastern North America. Agricultural and Forest Meteorology 151, 521–528, http://dx.doi.org/10.1016/j.agrformet.2010.12.013. Betts, R.A., Ball, J.H., 1997. Albedo over the boreal forest. Journal of Geophysical Research 102 (96), 901–909, http://dx.doi.org/10.1029/96JD03876. Betts, R.A., Falloon, P.D., Goldewijk, K.K., Ramankutty, N., 2007. Biogeophysical effects of land use on climate: model simulations of radiative forcing and large-scale temperature change. Agricultural and Forest Meteorology 142 (2–4), 216–233, http://dx.doi.org/10.1016/j.agrformet.2006.08.021. Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320 (5882), 1444–1449, http://dx.doi.org/10. 1126/science.1155121.
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Rautiainen, M., Stenberg, P., 2005. Application of photon recollision probability in coniferous canopy reflectance simulations. Remote Sensing of Environment 96, 98–107, http://dx.doi.org/10.1016/j.rse.2005.02.009. Rautiainen, M., Mõttus, M., Stenberg, P., 2008. Crown envelope shape measurements and models. Silva Fennica 42 (1), 19–33. Rautiainen, M., Stenberg, P., Mõttus, M., Manninen, T., 2011a. Radiative transfer simulations link boreal forest structure and shortwave albedo. Boreal Environment Research 16, 91–100. Rautiainen, A., Wernick, I., Waggoner, P.E., Ausubel, J.H., Kauppi, P.E., 2011b. A national and international analysis of changing forest density. PLoS One 6 (5), e19577. Rautiainen, M., Mõttus, M., Heiskanen, J., Akujärvi, A., Majasalmi, T., Stenberg, P., 2011c. Seasonal reflectance dynamics of common understory types in a northern European boreal forest. Remote Sensing of Environment 115 (12), 3020–3028, http://dx.doi.org/10.1016/j.rse.2011.06.005. ˜ ´ Z., SchaepRautiainen, M., Mõttus, M., Yánez-Rausell, L., Homolová, L., Malenovsky, man, M.E., 2012. A note on upscaling coniferous needle spectra to shoot spectral albedo. Remote Sensing of Environment 117, 469–474. Repola, J., 2008. Biomass equations for birch in Finland. Silva Fennica 42 (4), 605–624. Repola, J., 2009. Biomass equations for Scots pine and Norway spruce in Finland. Silva Fennica 43 (4), 625–647. Roberts, D., Ustin, S., Ogunjemiyo, S., Greenber, J., Dobrowski, S., Chen, J., Hinckley, T., 2004. Spectral and structural measures of northwest forest vegetation at leaf to landscape scales. Ecosystems 7 (5), 545–562. Smolander, S., Stenberg, P., 2003. A method to account for shoot scale clumping in coniferous canopy reflectance models. Remote Sensing of Environment 88, 363–373, http://dx.doi.org/10.1016/j.rse.2003.06.003. Smolander, H., Stenberg, P., Linder, S., 1994. Dependence of light interception efficiency on structural parameters. Tree Physiology 14, 971–980. Snyder, P.K., Delire, C., Foley, J.A., 2004. Evaluating the influence of different vegetation biomes on the global climate. Climate Dynamics 23 (3/4), 279–302, http://dx.doi.org/10.1007/s00382-004-0430-0. Stenberg, P., Linder, S., Smolander, H., 1995. Variation in the ratio of shoot silhouette area to needle area in fertilized and unfertilized Norway spruce trees. Tree Physiology 15 (11), 705–712. Stenberg, P., Kangas, T., Smolander, H., Linder, S., 1999. Shoot structure, canopy openness, and light interception in Norway spruce. Plant, Cell and Environment 22 (9), 1133–1142. Stenberg, P., Nilson, T., Smolander, H., Voipio, P., 2003. Gap fraction based estimation of LAI in Scots pine stands subjected to experimental removal of branches and stems. Canadian Journal of Remote Sensing 29 (3), 363–370. Stenberg, P., Rautiainen, M., Manninen, T., 2004. Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica 38, 3–14. Thuillier, G., Hersé, M., Labs, D., Foujols, T., Peetermans, W., Giliotay, D., Simon, P.C., Mandel, H., 2003. The solar spectral irradiance from 200 nm to 2400 nm as measured from the Atlas and Eureca missions. Solar Physics 214, 1–22. Widlowski, J.L., Taberner, M., Pinty, B., Bruniquel-Pinel, V., Disney, M., Fernandes, R., Gastellu-Etchegorry, J.-P., Gobron, N., Kuusk, A., Lavergne, T., Leblanc, S., Lewis, P.E., Martin, E., Mõttus, M., North, P.R.J., Quin, W., Robustelli, M., Rochdi, N., Ruiloba, R., Soler, C., Thompson, R., Verhoef, W., Verstraete, M.M., Xie, D., 2007. Third radiation transfer model intercomparison (RAMI) exercise: documenting progress in canopy reflectance models. Journal of Geophysical Research 112 (D9), 1–28, http://dx.doi.org/10.1029/2006JD0078.
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Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel
Relationship between forest density and albedo in the boreal zone Petr Lukeˇs ∗ , Pauline Stenberg, Miina Rautiainen Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland
a r t i c l e
i n f o
Article history: Received 28 January 2013 Received in revised form 12 April 2013 Accepted 14 April 2013 Available online 16 May 2013 Keywords: Radiative transfer Forest reflectance model Boreal forest Albedo Biomass
a b s t r a c t The relationship between albedo and forest areas is complex. Little is known about the driving factors of albedo in the boreal zone. Using a radiative transfer model and an extensive forest inventory database, we simulated albedo of forest stands composed of the most abundant tree species of Fennoscandia – Scots pine, Norway spruce and Silver birch. The physically-based radiative transfer model allowed us to uncouple the driving factors of the forest albedo. We analyzed separately how biomass, canopy cover, and species composition influence the shortwave albedo of a boreal forest. The albedos differed significantly between species and increased with solar zenith angle. The lowest values were observed for spruce stands, followed by pine stands and the highest values were observed for birch stands. Diurnal courses of albedo were tightly related to forest density as quantified by biomass or canopy cover. The albedos generally decreased with increasing stand biomass and canopy cover whereas the sensitivity to solar angle increased as the stands became denser. The sharpest decrease in albedo was observed at low biomass values, after which the albedo remained relative stable. The strength of the relationships was weaker for larger solar zenith angles. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Changes in the amount of forest cover and biomass can have diverse effects on global climate and carbon sequestration via various feedback mechanisms, such as fluctuations in the land surface albedo and effects on the global water cycle. On the other hand, changes in climate directly affect the functioning of forests via the frequency of occurrences of natural disturbances, CO2 fertilization, and alterations in the length of the growing season (Betts et al., 2007). Among terrestrial biomes boreal forests have the greatest effect on annual mean global temperature (Snyder et al., 2004). The on-going increase in boreal forest biomass in Europe and parts of Asian Russia can influence the global climate not only through carbon fixation but also through altering the albedo. However, the link between forest land and its albedo is complex: very little is known about the influence of natural disturbances and human activities (such as forest management procedures) on albedo. Albedo perturbations due to natural forest disturbances can either enhance or reduce the positive radiative forcing from CO2 efflux (O’Halloran et al., 2012; Bernier et al., 2011). In regions seasonally covered by snow such as the boreal zone, removal of forest canopy will lead to an increase in albedo in winter; snow
∗ Corresponding author. Tel.: +358 09 191 58189. E-mail addresses: petr.lukes@helsinki.fi, [email protected] (P. Lukeˇs). 0304-3800/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecolmodel.2013.04.009
covered forest floors significantly affect the total canopy albedo (Manninen and Stenberg, 2009). Furthermore, the effects of stand age and development stage on albedo need to be considered (Bonan, 2008). In managed boreal forests, forestry practices affect the albedo not only through changes in biomass and canopy cover but also by altering the stand structure (Rautiainen et al., 2011a). A similar canopy cover or biomass can result from a range of forest structures, which cause different albedos. Whereas the general difference in the albedo of coniferous and deciduous forests has been long established (e.g. Betts and Ball, 1997), the reasons behind this are still partly unknown. Moreover, as there are indications that the currently conifer-dominated boreal forests are gradually shifting towards including more deciduous tree species, it is ever more important to understand the role of species composition on forest albedo. As the global forest area and biomass change independently (Rautiainen et al., 2011b), their effects on forest albedo need to be analyzed separately. Neither local albedo measurements nor satellite-based albedo products can explain the causality between small-scale environmental management scenarios and changes in albedo. Thus, forest reflectance models validated with satellite remote sensing data is the only possible method for linking quantitative changes in vegetation structure to albedo for large geographical regions. Forest reflectance models are parameterized using mathematical descriptions of canopy structure (e.g. leaf area index, tree height, crown dimensions, stand density), optical properties of leaves and forest floor, and spectral and angular properties of incoming radiation.
P. Lukeˇs et al. / Ecological Modelling 261–262 (2013) 74–79 Table 1 Tree species composition and understory types for the study sites Puumala, Saarinen and Hyytiälä.
Number of stands Dominant species (%) Pine Spruce Birch Understory type (%) Mesic Herb-rich Xeric
Puumala
Saarinen
361
326
Hyytiälä 8
67 26 7
28 53 19
4 43 53
89 0 11
96 3 1
50 38 12
Using these models, the spectral and broadband albedos of a forest can be calculated from more readily measurable variables such as forest structure and leaf optical properties. Here, we investigate the influence of forest biomass, canopy cover and species composition on the shortwave albedo of boreal forests using a forest reflectance model which uses routine forest inventory variables as input. We use an extensive forest inventory database collected in Finland covering the natural variation in stand structures. 2. Materials and methods 2.1. Study stands We simulated the albedo for 695 boreal forest stands located in three sites in Central and Eastern Finland, named Puumala, Saarinen and Hyytiälä. The stands represent the typical range in stand structures, development classes and site fertility types of managed boreal forests in Finland, and are dominated by the most abundant tree species in Northern Europe i.e. Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst) and birches (Betula pendula Roth or Betula pubescens Ehrh.) (Table 1). The forest inventory database available as input for the albedo simulations included leaf area index (LAI) and species-specific values of stand density (N), and medians of diameter at breast height (DBH), tree height (H) and crown length (LCROWN ). The understory type was assigned to each forest stand based on its site fertility class. The stands and measurements are described in more detail by Stenberg et al. (2004) and Korhonen et al. (2011). The two inputs for albedo simulations which were not directly measured were the crown radius (CR ) and total aboveground biomass. CR was calculated using an allometric relationship between DBH and CR developed by Jakobsons (1970) for pine, spruce and birch of northern Sweden (latitudes > 60◦ ). Total aboveground biomass of simulated stands was estimated using the recently developed Finnish national multivariate models for birch (Repola, 2008), pine and spruce (Repola, 2009). Basic structural parameters of all forest stands (N = 695) are given in Table 2, and the structural parameters of monospecific stands (N = 291) in Table 3. The optical properties (directional-hemispherical reflectance and transmittance factors) of needles and leaves for the three species were obtained from a spectral database measured by Lukeˇs et al. (2013) in boreal Finland (Fig. 1a). For the two coniferous species, the shoot was chosen as the basic scattering element (Nilson and Ross, 1996), i.e. we used shoot spectra (instead of needle spectra) as input in the albedo simulations. Species-specific shoot spectra were obtained from needle spectra according to a previously published methodology (Rautiainen et al., 2012; Smolander and Stenberg, 2003) using average values of the shoot to total needle area ratio, STAR (Oker-Blom and Smolander, 1988). The STAR values used were 0.147 for pine (Smolander et al., 1994) and 0.161 for spruce (Stenberg et al., 1995).
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Optical properties of the forest understory were based on a database collected in Finland (Rautiainen et al., 2011c) covering typical forest understory types from herb-rich green understories to xeric lichen types (Fig. 1b). For each study stand, we assigned an understory spectrum (xeric, mesic or herb-rich) according to its site fertility class. Also bark and trunk optical properties were based on a previously published database (Lang et al., 2001). 2.2. Albedo simulations Albedo simulations for different solar zenith angles (SZA) were performed using the recently modified version (Mõttus et al., 2007) of the Forest Reflectance and Transmittance Model (FRT) (Kuusk and Nilson, 2000). FRT is a hybrid type of radiative transfer model, i.e. it includes properties of both geometric-optical and radiative transfer equation based models. The forward simulations of albedo for a large number of stands with a complex structure are relatively fast with the FRT because the model is computationally efficient and its parameterization is based on standard forest inventory data. More importantly, it is able to accurately simulate the spectral fluxes of a forest (Widlowski et al., 2007). Several tree classes with different structure, density and optical properties of foliage can be defined in FRT in order to simulate mixed stands. We simulated either one, two or three tree classes depending on the species composition of the study stand. Tree crowns were simulated with ellipsoid crowns which have been found to represent well crown shape and volume in our study species (Rautiainen et al., 2008; Mõttus et al., 2006). As described previously, the input parameters by species were obtained directly from the inventory database or derived using allometric equations (Table 4). The optical properties of leaves, shoots and bark were parameterized according to measured values (see Section 2.2) (i.e. one average spectrum of foliage and bark for each tree species). The forest floor was considered a Lambertian surface with a mesic, herb-rich or xeric type spectrum. In this study, we simulated the black-sky albedo, also known as directional-hemispherical albedo which has been specified as the product required for climate change purposes (GCOS, 2004). Forest albedo was simulated for two extreme solar zenith angles (40◦ and 70◦ ) during midsummer at latitudes corresponding to the study sites (around 61◦ ). In addition, the hourly diurnal course of albedo during summer solstice (DOY = 172) was simulated for hourly solar zenith angles between 6 am and 6 pm of apparent solar time. The albedo simulations were run at a 5 nm spectral resolution from 400 nm to 2400 nm. A 12 × 12 quadrature was used to integrate over all the viewing zenith and azimuth angles in the hemisphere. The broadband shortwave albedo was approximated as a sum of spectral albedos weighted by the incoming solar irradiances at the corresponding wavelengths. We used solar irradiance measurements which are recommended as the reference exo-atmospheric solar irradiance spectrum by the Committee on Earth Observation Satellites (CEOS) (Thuillier et al., 2003). Although our simulated spectral range (400–2400 nm) is somewhat narrower than the theoretical definitions of total shortwave broadband albedo (300–4000 nm), it covers the bulk part (ca. 98%) of the solar irradiance and thus gives a good approximation of total broadband albedo. 3. Results 3.1. The influence of species composition on albedo First, we focused on monospecific forest stands, i.e. stands with a 100% composition of pine, spruce or birch. From the original 695
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Table 2 Basic structural characteristics of the study stands (n = 695). Mean values and standard deviations (in parentheses) shown.
Stand density (trees/ha) DBH (cm) H (m) Lcrown (m) CR (m) Total aboveground biomass (kg/tree)
Pine
Spruce
Birch
891 (675) 14.60 (4.70) 12.10 (3.20) 6.53 (1.87) 1.27 (0.28) 80.00 (68.57)
686 (788) 16.60 (6.44) 13.80 (4.56) 8.77 (3.42) 1.44 (0.31) 115.64 (100.1)
491 (661) 11.32 (5.35) 10.33 (4.03) 6.47 (2.62) 1.40 (0.37) 46.46 (63.27)
Table 3 Basic structural characteristics of monospecific stands (n = 291). Mean values and standard deviations (in parentheses) shown.
Stand density (trees/ha) DBH (cm) H (m) Lcrown (m) CR (m) Total aboveground biomass (kg/tree)
Pine
Spruce
Birch
1084 (642) 13.77 (3.83) 11.15 (2.88) 5.93 (1.51) 1.22 (0.23) 59.84 (40.23)
806 (1076) 19.40 (6.46) 15.75 (4.15) 10.90 (3.26) 1.60 (0.31) 167.01 (105.6)
1167 (1124) 7.29 (3.46) 7.06 (3.90) 4.03 (1.97) 1.12 (0.24) 14.80 (17.69)
Fig. 1. The average single scattering albedo of pine and spruce needles and birch leaves (a) and the average hemispherical-directional reflectance factor (HDRF) of forest understory of mesic, herb-rich and xeric type (b).
stands there were 179 pure pine, 97 pure spruce and 15 pure birch stands. The mid-day albedos (SZA = 40◦ ) of monospecific forest stands differed significantly between species (Fig. 2). The lowest values were observed for spruce (average albedo of 0.11 with standard deviation of 0.03), and the highest for birch (0.22 ± 0.01). The simulated albedos of pine stands (0.14 ± 0.02) were between spruce and birch stands. We studied the impact of species composition on the albedo of mixed stands composed of spruce with either birch or pine as admixtures. We analyzed two cases: (a) the fraction of birch and (b) the fraction of pine in a spruce forest (Fig. 3). The fraction was expressed as the ratio of the number of birch (or pine) trees per hectare to the total number of trees per hectare. The average albedo
of mixed spruce-birch stands increased from 0.1 to 0.18 when the fraction of birch increased from 20% to 90%. A slight increase in albedo also occurred in the mixed spruce-pine stands with increasing fraction of pine, but the relationship was not as tight as for birch. 3.2. Diurnal variation in albedo The diurnal variation in albedo was analyzed using monospecific stands. The albedos simulated for the day of summer solstice stayed relatively constant from 9 am to 4 pm (SZA between 39◦ and 57◦ ) but clearly increased towards morning and evening hours (SZA larger than 57◦ ) (Fig. 4). The diurnal variation in albedo
Table 4 Additional parameters required by the FRT model. Pine
Spruce
Birch
References
Specific leaf weight (g/m )
161
202
57
Branch to total leaf area ratio
0.18
0.18
0.15
Tree distribution parameter Shoot length (cm) Shoot shading coefficient
10 0.59
1.2 5 0.64
Pine: Palmroth and Hari (2001), spruce: Stenberg et al. (1999), birch: Kull and Niinemets (1993) Pine: Stenberg et al. (2003), spruce and birch according to Nilson (1999) Nilson (1999)
40 1
2
Calculated as 4 × STAR for pine and spruce Smolander et al. (1994) and Stenberg et al. (1995)
P. Lukeˇs et al. / Ecological Modelling 261–262 (2013) 74–79
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50 Pine Spruce Birch
45
Number of stands
40 35 30 25 20 15 10
0.24
0.23
0.22
0.2
0.21
0.19
0.18
0.17
0.16
0.15
0.14
0.13
0.12
0.1
0.11
0.09
0
0.08
5
DHR Fig. 2. Albedo of monospecific pine, spruce and birch stands simulated by the FRT model.
was characterized by the ratio of morning to midday values) and increased with canopy cover (r = 0.86–0.89) for all species (Fig. 5). 3.3. The influence of biomass, leaf area index and canopy cover on albedo A decrease in albedo at SZA = 40◦ with increasing stand biomass, LAI, and canopy cover was observed for all species (Fig. 6). The relationship between albedo and these measures of forest density were similar with each other but the tightest for LAI. The sharpest decrease in albedo with increasing forest density was observed for sparse canopies. For denser canopies the albedo values remained relatively stable. Pine stands were separated into two groups based on their understory type: mesic and xeric. Stands with mesic understory had a similar relationship between forest density and albedo as spruce. For pine stands with xeric understory, on the other hand, the dependency was non-existent. The relationships
Fig. 4. Hourly average albedo and its standard deviation (vertical bars) for the monospecific pine, spruce and birch stands.
became weaker for large solar zenith angles and were almost flat at SZA = 70◦ (results not shown). 4. Discussion The boreal forests in Fennoscandia are typically composed of evergreen coniferous species (Scots pine and Norway spruce) with small proportions of deciduous birch. For example, the forests of Finland are composed of 65% pine, 24% spruce and 11% broadleaved species, mainly birch (Metla, 2011). Our extensive simulations of boreal forest albedo confirmed the observation from many previous studies (e.g. Betts and Ball, 1997) that there is a clear difference in albedo between different tree species, 1.4 1.3
Albedo ratio
1.2 1.1 1 0.9 0.8 0.7
Birch Coniferous
r=0.89 r=0.86
0.6 0
0.2
0.4
0.6
0.8
1
Canopy cover Fig. 3. The influence of fraction of birch or pine in mixed spruce-birch and sprucepine on the albedo of spruce stands.
Fig. 5. The relationship between canopy cover and albedo ratio for monospecific coniferous (pine and spruce combined) and birch stands. The albedo ratio is defined as forest albedo at SZA = 70◦ divided by forest albedo at SZA = 40◦ .
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Fig. 6. The relationship between albedo (at SZA = 40◦ ) and total aboveground biomass (a), LAI (b) and canopy cover (c) for monospecific pine, spruce and birch stands. Pine stands have been separated into two classes, mesic and xeric, based on their understory type.
especially between broadleaved species and spruce (Fig. 2). The clear differences in the albedos of monospecific spruce, pine and birch stands show that the composition and abundance of different species in mixed stands will significantly affect their albedo. The albedo of mixed spruce-birch stands doubled when the fraction of birch increased from marginal to dominant (Fig. 3). The fraction of pine, on the other hand, had a very small effect on the albedo of mixed spruce-pine stands. The lower albedo of coniferous species has been attributed to their hierarchical clumped structure which causes photons to be trapped within shoots and crowns (Rautiainen and Stenberg, 2005), as well as to the typically low single scattering albedo of needles (Roberts et al., 2004; Lukeˇs et al., 2013). Of the two coniferous species, spruce stands had the lower albedo, which in part may be explained by typically higher values of foliage biomass (and LAI) and canopy cover. During most of the day (SZA = 39◦ –57◦ ), the mean albedos remained rather stable (Fig. 4). They increased only in early morning or late evening, i.e. at large solar zenith angles. At these angles, however, the incoming levels of solar irradiance are very low. Thus, when calculating temporal courses of albedos, the mid-day values will have the largest weight. It should be observed, however, that the sensitivity to solar zenith angle, and thus temporal variation, in albedo increases with forest density (Fig. 5). The albedo was tightly related to measures of forest density (Fig. 6). However, for similar values of biomass, LAI and canopy cover, there were still distinctive differences between the albedos of the pine and spruce stands. This can be hypothesized to result from the lower needle single scattering albedo of spruce than of pine (Fig. 1) and the longer crowns of spruce canopies (Table 2). Although the albedos of monospecific stands generally decreased with forest density, their sensitivity to SZA increased (Fig. 5). We may, therefore, expect stronger diurnal fluctuations in albedo for dense stands with more closed canopies and higher biomass values. In boreal forests of Fennoscandia, 50% of the stands have a canopy cover lower than 0.5 (DeFries et al., 1995). This also turned out to be the most sensitive region for albedo changes (Fig. 6), arguably due to the significant role of forest understory. The understory type is closely linked to the fertility, species composition and geographic location of the stands. While the typical understory layers in the southern boreal region in, for example, Fennoscandia belong to mesic and herb-rich types, the lichen dominated xeric
type is common for the northernmost boreal forests dominated by pine. In general, the less fertile understory site types decrease the forest albedo, and the effect is larger the more open is the stand. The influence of understory on stand albedo was evident at small solar zenith angles and low biomass values (Fig. 6). 5. Conclusions Forest management practices, such as logging patterns or growing monospecific or mixed forests may have a significant influence on the albedo of the boreal biome. However, the influence of the resulting forest structure and species composition on the albedo of these forests has not been studied before using an extensive forest inventory database. In this study, we identified factors driving boreal forest albedo using a theoretical model. We show that species-specific stand albedos and their diurnal courses are tightly linked to forest density. The albedos differed significantly between species with the lowest values being observed for spruce and the highest for birch. From the forest management perspective, our results suggest that an increase in albedo can be achieved by (1) increasing the proportion of birch in conifer-dominated forests and (2) managing forests to have a low stand density throughout the rotation period. Acknowledgements The study was funded by the Academy of Finland. We thank Dr. Matti Mõttus and Dr. Janne Heiskanen for fruitful discussions. References Bernier, P.Y., Desjardins, R.L., Karimi-Zindashty, Y., Worth, D., Beaudoin, A., Luo, Y., Wang, S., 2011. Boreal lichen woodlands: a possible negative feedback to climate change in eastern North America. Agricultural and Forest Meteorology 151, 521–528, http://dx.doi.org/10.1016/j.agrformet.2010.12.013. Betts, R.A., Ball, J.H., 1997. Albedo over the boreal forest. Journal of Geophysical Research 102 (96), 901–909, http://dx.doi.org/10.1029/96JD03876. Betts, R.A., Falloon, P.D., Goldewijk, K.K., Ramankutty, N., 2007. Biogeophysical effects of land use on climate: model simulations of radiative forcing and large-scale temperature change. Agricultural and Forest Meteorology 142 (2–4), 216–233, http://dx.doi.org/10.1016/j.agrformet.2006.08.021. Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320 (5882), 1444–1449, http://dx.doi.org/10. 1126/science.1155121.
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