Effects of a Windthrow Disturbance on the Carbon Balance of a Broadleaf Deciduous Forest in Hokkaido, Japan

Home , Windthrow

Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | X class copernicus.cls. E T A 2 1 , and H. Utsugi 1 , Y. Mizoguchi 1

Forestry and Forest Products Research Institute, Tsukuba, 305-8687, Japan Hokkaido Research Center, Forestry and Forest Products Research Institute, 7 Hitsujigaoka, Correspondence to: K. Yamanoi ([email protected]) Toyohira-ku, Sapporo, 062-8516, Japan 2 1 K. Yamanoi forest in Hokkaido, Japan

carbon balance of a broadleaf deciduous Effects of a windthrow disturbance on the Date: 2 November 2015 with version 2015/04/24 7.83 Copernicus papers of the L Manuscript prepared for Biogeosciences Discuss. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) increased by before the disturbance 1 − yr S. senanensis 2 − and g C m ﬂux within the forest in detail. Damaged trees 2 2 Sasa kurilensis 2 years after the disturbance, respectively. Before CO 1 − yr 2 − g C m 97 − ﬂux has been measured using the eddy covariance method in a deciduous increased rapidly and contributed to the total GPP after the disturbance. The 2

CO Sasa

various kinds of disturbances,well as we disturbance emphasized type the in the importance carbon of balance. forest management as paring the carbon uptake efﬁciency at the study site with that at others, including those with the decomposition of residues.remaining The at forest the study management, site, which strongly affected resulted the in carbon balance the over dead the years. trees When com- debris. The carbon balance after the disturbance was controlled by the new growth and annual GPP only decreasednual by Re 6 % increased just by after 39 % the mainly disturbance. because On of the the other decomposition hand, of the residual an- coarse-wood thesis of factors of 2.4 and 1.7, respectively, in 3 years subsequent to the disturbance. The photosyn- a net carbon source.index Because and of biomass increased of light the intensity undergrowth at ( the forest ﬂoor, the leaf area the disturbance, the forest was an evident carbon sink, and it subsequently transformed to net ecosystem production wereand 1350, 1262, 1359, 975, and and 375 by forest management. Gross primary production (GPP), ecosystem respiration (Re), and biometrical method to demonstrate the amounted to 40 % of all trees, and they remained on site where they were not extracted accidental damage by the strong typhoon, Songda, in 2004 occurred. We also used the broadleaf forest (Japanese white birch, Japanese oak, and castor aralia) in Hokkaido, where and windthrow is a typicalAsia. disturbance The event affecting the forest carbon balance in eastern bon sequestration stage. The net carbon releases that occur result from forest disturbance, Forests play an important role in the terrestrial carbon balance, with most being in a car- Abstract Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | in- 2 may be CO years 3 concentration. Therefore, to determine the carbon balance in various forest

peak in carbon sequestration. Amiro et al. (2010) summarized more than 180 site years event, the forest is typically a net carbon source over the initial years, followed by a broad following a disturbance (harvesting) in five forest ecosystems across Europe. After each occurs with some delay, but thetake. release Magnani is et nevertheless al. rapid (2007) relative demonstrated to the the age-related net dynamics carbon of up- the carbon balance released within a few hours. In cases of disturbance, except for fire, most carbon release a few months, e.g., byFor forest harvesting, example, and in bypass a the fire, heterotrophic chain carbon of fixed respiration. over a period of a few decades to 300 management. The third type may impose impacts within a few hours, e.g., by fire, or within age within a day, e.g.,dead-wood by matter windthrow, or resulting within from a the few impact months, e.g., may by remain impact on by site insects. if All not extracted by forest ecosystem, gradually changing the carbon balance. The second type may impose dam- by fire and harvesting. The first disturbance type may impose persistent stresses on the crease, (2) disturbances thatwindthrow, or act (3) as disturbances where a the disruption C of and N C are and exported N from the cycles, ecosystem, e.g., e.g., by insects or as follows: (1) continuous forcing of the C and N cycles, e.g., by temperature or and carbon accumulation into thetend soil to is result tied from to forest forest age. disturbances. In Schulze contrast, (2006) net classified carbon ecosystem releases disturbances weather conditions. The net carbon uptake is a slow phenomenon because of tree growth in a carbon sequestration stagebon when forest balance destruction in is such not taken forests into is account. stable, The car- with anomalies occurring in relation to interannual Law et al., 2002; Hirata et al., 2008). These measurements indicated that most forests are ecosystems, eddy covariance measurements have been performed (Valentini et al., 2000; forest (Körner, 2003). A netmospheric carbon uptake or release by forests has an impact on the at- 90 % of all biomass is stored in trees and 50 % of terrestrial organic matter is stored in Forests play a particularly important role in terrestrial carbon sequestration because almost 1 Introduction Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C, for all Mt (Knohl 2 − years g C m of windthrown stem during the first year. 3 Mt C million m after a windthrow event. years . The reduction in the carbon sink scaled to 2 (Schulze et al., 1999) and 192 4 2 km − g C m for most. Goetz et al. (2012) assessed the forest carbon dy- years C. This amount is equivalent to 50–140 % of the net annual carbon sink in Tg

Windthrow is the most signiﬁcant disturbance in eastern Asia, which is a humid region. Although many types of disturbance have an inﬂuence on the carbon balance, windthrow

ecosystems. For example, Typhoon Toyamaru, which was the most severe typhoon event in Typhoons are a typical windthrow event inJapan, causing catastrophic damage to forest et al., 2002) over a 3-month period in summer 2 sia, the spruce forests released 180 Storm Lothar in 1999equating reduced to approximately the 30 European % carbon of the balance net by biome approximately production 16 in Europe. In European Rus- the whole windthrown area was estimated at approximately 3 wood over an area of approximately 2 720 (Nilsson et al., 2004;drun, Usbeck which et hit Sweden al., in 2010). 2005, resulted Lindroth in et approximately 66 al. (2009) reported that storm Gu- US forests. In western Europe, windthrow storm events are important forest disturbances ricane Katrina in 2005 destroyedloss 320 of million 105 large trees, corresponding to a total biomass events by hurricanes are intensive and frequent. Chambers et al. (2007) estimated that Hur- is one of thetiﬁcation most of inﬂuential the ones. change However, in few the reports carbon balance have caused described by the windthrow. direct In the quan- USA, windthrow

tion period, size, intensity, severity, and residuals (Turner, 2010). types. Therefore, the long-term carbonshows balance special is and affected temporal by dynamics a and disturbance is regime, composed which of frequency, return interval, rota- tain factors driving post-disturbance carbon source–sink dynamics across all disturbance namics following disturbances of fire, insects,disturbance and severity harvest and in North history America. as They key identified factors but recognized that there are highly uncer- ecosystems and by 10 America. Net ecosystem production (NEP)lowing showed a a stand-replacing carbon disturbance, loss only from returning all to ecosystems a fol- carbon sink after 20 disturbances including fire, harvest, thinning, insect infestations, and windthrow in North of eddy covariance measurements of carbon flux made at forest chronosequences after Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 km of stem wood 3 million m (2000–2003). Seasonal and inter- years by a forest ecosystem has been measured of forest area and 27 2 5 2 CO km . While IPCC (2013) reported the potential in future 1 − yr 2 − g C m flux were evaluated and characterized. We used the biometrical 2 after disturbances of the Japanese larch forest. Ito (2010) evaluated 2 CO − g C m 80 −

In this study, the uptake and release of

revegatation process resulting from the windthrow disturbance. forest. By coincidence, the monitoredin forest 2004. was Subsequently, damaged we by focused the on strong the typhoon, change Songda, in the carbon balance under the natural method with the eddy covariance method to demonstrate the detailed carbon balance in the on the carbon balanceannual of variations this in forest for the first 4 since the year 2000 using the eddy covariance technique. Kitamura et al. (2012) reported ral and spatial variation, itperiod is both uncommon before and for after flux a measurement disturbance. to continue for an extended carbon balance. Although a disturbance is a complicated process associated with tempo- strated increases of typhoon intensityoccasional with large global windthrow warming event may in partly the affect western the interannual North variation Pacific. in An the terrestrial tropical cyclone frequency and intensity was low confidence, Tsuboki et al. (2015) demon- ous broadleaf forest. Thecarbon biomass gain of by leaves nearly decreased 200 by 10–20 %, lowering the canopy the impact of defoliation caused by a typhoon event on the carbon balance in a decidu- before to itoring of the carbon flux usingtems. the Sano eddy covariance et method al. in (2010) wind-disturbed forest reported ecosys- that NEP during the growing season changed from 159 (Hokkaido Forest Research Institute, 2004). There are few reports detailing long-term mon- phoon Songda (the triggerof event forest for area, this which study) caused also dramatic hit damage Hokkaido but and only damaged 5 % 370 of that of Typhoon Toyamaru in Hokkaido, the northernmost island of Japan, in 1954 (Tamate et al., 1977). In 2004, Ty- Japan’s recorded history, damaged 7 500 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C in N, ◦ 0 and m 1 59 ◦ − ) dominantly ), castor aralia trees ha ) to mid- and late- ), and Japanese lin- % of the basal area in C in January to 20.1 75 ◦ old in 2002. japonica S. senanensis > grosseserrata 5.1 var. − years and Acer mono var. ) of the Hokkaido Research Center, ha , and maximum snow depth was 1.37 6 Sasa kurilensis mm Betula platyphylla Quercus mongolica diameter at breast height (DBH) were 672 . The soil parent material of this area is predominantly vol- cm ◦ (Thunb.) Koidz), painted maple ( ; AsiaFlux site code: SAP) in Sapporo, Japan. The site is located . l . s . )) forest. The first two species accounted for m a E; 182 0 in 2003, respectively. The oldest white birch was 90 C, and the monthly mean temperature ranges from

◦ Tilia japonica 23 m

◦ The strong Typhoon Songda (18th of the season) struck northern Japan on 8 Septem-

Kalopanax septemlobus tree biomass (Takahashi et al., 2009;at Utsugi the et site. al., However, 2009). the Large canopy damage gaps was were heterogeneously formed distributed throughout the forest. nant tree species. The subsequent typhoon removed 33 % of the tree canopy and 28 % of ber 2004. Many canopy trees(Fig. 1). were uprooted Prior or to broke the off windthrow disturbance, by the strong canopy winds was at almost the closed SAP with site the domi- 18.3 covered the forest ﬂoor andand some mean herbaceous species tree partly height covered over it. 5 The stand density 2003 (Utsugi et al., 2005). Dwarf bamboo ( ( den ( successional species (Japanese oak ( tury (1874, 1883,early 1887, successional and Japanese white 1888). birch ( The forest represents the transition stage from an secondary deciduous broadleaf forest, regenerated after wildﬁres in the late 19th cen- canic ash, and the soil type is Andosol (Ishizuka et al., 2006). The forest type is mature February 2000 (Mizoguchi etan al., average 2014a). inclination The of terrain 6.5 gently slopes to the northwest, with in August. The annual precipitation is 945 Forestry and Forest Productsis Research 7.3 Institute (FFPRI). The mean annual temperature within the Hitsujigaoka Experimental Forest (147 This study was141 conducted at the Sapporo forest meteorology research site (42

2.1 Site description 2 Materials and methods Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | m on a 41 m and was reg- 1 , and, therefore, − ) standard gases in ). Sampling air from min m L min ppm ) using a digital data log- Hz (450 (5 2 s in inner diameter. Sample air was CO mm 7 . The IRGA was calibrated automatically once min in length and 6 m concentrations. An aspirated thermohygrometer (HMP-45A, 2 . The sampling interval of each height was 2 CO 1 − . The residual air was released from an exhaust port. Water vapor in 1 − L min L min concentration were measured using another IRGA (LI-6262, LI-COR) with a valve 2

ﬂux was measured using an eddy covariance system at a height of 28.5

CO 2 Meteorological conditions were measured in and above the forest canopy. Air tem-

perature and humidity were measured using an aspirated thermohygrometer (HMP-45D, a day. one cycle of the system equated to 10 each height was dehumidified usinga the flow same rate air of dryer, 1.8 and was pushed into the IRGA at switching unit at five sampling heights (3.6, 10.5, 16.3, 20.1, and 29.6 the and Watanabe (2001). Thesubsequently modified system for in long-term flux FFPRI monitoring (Ohtani FluxNet et sites, al., 2001). including Vertical profiles the of SAP site, was ger (DRM3, TEAC, Japan). Details of the flux system are reported in the study by Yasuda was calibrated automatically once aan day air using balance. The zero sensor and signals were recorded every 0.2 the sample air was removed with an air dryer (MD-110-48F, Perma Pure, USA). The IRGA pushed into a mass flowulated controller at at a 2.0 flow rate of approximately 9.5 a polytetrafluoroethylene tube of 40 the IRGA in a cabin located at the ground level. The inlet and IRGA were connected by Vaisala, Finland) that measured relativesame humidity height and as air the temperature SAT. was The mounted air at inlet the was installed behind the SAT, and air was drawn to measured atmospheric sonic anemometer (SAT: DA600-3T or DA600-3TV, SONIC, Japan)tor that measured components wind and vec- a closed-path infrared gas analyzer (IRGA: LI-6262, LI-COR, USA) that tall scaffold tower at the center of the SAP site. The system consisted of a three-dimensional CO 2.2 Flux and meteorological measurements began recovering under the natural mechanisms of the ecosystem. All dead trees remained on site and were not extracted by forest management. The forest Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 CO from the temporal profile data, the rate 2 min using the eddy covari- CO min ) and above the undergrowth m concentration. Tests were run on 2 CO 8 . Photosynthetically active radiation (PAR) was measured using quan- storage in the canopy (Sc) was calculated every 30 m storage in an air column between the ground level and the height of the 2 2 CO CO

ﬂux above the canopy (Fc) was calculated every 30 2

). CO m

The observations commenced in August 1999. The observational infrastructure was de-

eddy covariance systems. of change in change in rejected by the quality test mentioned above was 12 %. Using the tions due to instrument malfunction and maintenance was 10 %, and the amount of data whereas the other was(Foken a and series Wichura, of 1996; Vickers tests and in Mahrt, accordance 1997). with The the proportion quality of control missing procedure observa- all data to screen for data quality; one method used was visual inspection of the raw data, of air from thecorrelation inlet between to the vertical the wind cell velocity of and the the IRGA was optimized for the ﬁrst extremum of cross- an empirical transfer function. Linear trends were removed. The lag time of the sampling correction) were applied. Theconcentration in attenuation the loss closed-path of system (Leuning high-frequency and ﬂuctuations Moncrieff, 1990) in was the corrected with Gayner, 1991; Hignett, 1992), and the density correction theory of Webb et al. (1980) (WPL the effects of lateral wind on sonic velocity and of water vapor on temperature (Kaimal and The ance technique. Three-dimensional coordinate rotation (McMillen, 1988), corrections for 2.3 Data processing and analysis

The studies by Kitamura etdescription al. and (2012) additional and information Mizoguchi regarding et the al. meteorological (2014a) measurements. provide a more detailed stroyed by the typhoon in 2004 and reconstructed in the spring of 2005 (Nakai et al., 2004). (2.4 tum sensors (LI-190, LI-COR) at the top of the tower (41.3 Vaisala) at 29.6 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C ◦ (3) (4) (1) (2) are c is the ) to ex- ∗ max u threshold, , and ∗ u . In this study, max ∗ u , Ag 0 a after the disturbance as the 1 − m s is the increase in respiration for every 10 10 9 c, Q ) + Pd C and · were derived for three periods in a year (growth period, ◦ 0 a k , + ) . Ta , and max ) · is the daytime respiration rate. The variables 10 k Sc Ag c ( Q before the disturbance and 0.31 / + , 1 ) 0 exp( − R Fc 0 ( max R . m s − Ag = Re · = 10 + / Pd · Ta 10 is the respiration rate at 0 0 NEE is the light-use efﬁciency, Pd is the downward PAR above the canopy, Ag Q 0 a 0 NEP 0 − a R R

= = ( =

= threshold. NEE was equal to ecosystem respiration (Re) during the night. We expressed Data gaps during the nighttime NEP were inﬁlled with Re values calculated using Eq. (2), NEE was underestimated during low-turbulence atmospheric conditions, such as stable Net ecosystem exchange (NEE) is deﬁned as the sum of Fc and Sc during the average

∗

GPP was estimated as follows: light-saturated NEP, and constants and were derived daily for the previous 5 days. Gross primary production (GPP) where NEP

and those during the daytime were filled with NEP calculated as follows: (2) is valid during the day. Daytime was defined as the period from sunrise to sunset. defoliation period without snow,each and period. defoliation Daytime period Re with was snow) also and calculated using were Eq. constants (2), in with the assumption that Eq. rise in temperature. where Re Re in terms of air temperature (Ta): u we selected 0.29 clude flux under such conditions (Massmanwe examined and NEE Lee, at 2002). night, To determine which decreased the greatly with the depression of night periods. We applied data screening using the threshold of friction velocity (

NEP period and NEP is equal to negative NEE: Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) ha (5) H ) was C and ◦ 20m × and DBH for from 2000 to 2 H m 20m ) to the treetop. Each stratum m were measured. The crowns were G, H + Lf + 10 Ld ) after the disturbance. The DBH of all trees that ) + t1 20m , and DBH and × m AGB − 20m t2 is predation by herbivorous insects and was ignored in the for stem and branch and DBH for leaf in the allometric equations. G AGB H × ) plot established in 1978 before the disturbance and set up a 1.6 = ( 2 G 50m thick strata from the stump height (0.3 + × Lf m in the plots were measured every year from 2000 to 2012. Tree heights ( + is the aboveground biomass increment of surviving and recruiting trees, Lf is y 50m y 5 cm ∆ = ∆

The aboveground net primary production (ANPP) in a year was calculated as follows Biomass production at the stand level was estimated by summing up the biomass pro-

where litterfall from living trees, ANPP

(Clark et al., 2001): separated into leaf, branch, and other components (seed, ﬂower, and bud) for weighing. set up on the ground.resentative All of branches litterfall that during had the dropped on snowy to seasons. the The sheet litterfall were was collected oven-dried as at rep- 70 2003 in the growing seasons. In the snowy seasons, a large plastic sheet ( duction of individual trees,the which study was plots. obtained The by litterfall inventorying was the collected dimensions monthly of using trees 50 in traps of 0.48 dimensions, i.e., DBH were calculated from thefor the fresh entire weight tree, and and water the content. total These dry weight weights of were each summed component scaled positively with tree weight of each component was immediately measured. The dry weights of each component divided into 1 was divided into the tree biomass components of stem, branch, and leaf, and the fresh trees were felled at a height of 0.3 subjected to destructive analysis. Eight treesused of to birch, 10 determine of the oak, allometrics and 8 between of biomasses castor aralia and were tree dimensions. The sample each species were formulated. During the summer of 2001 and 2003, 26 sample trees were of all trees in the plot were measured in 2002. The relationships between plot composed of 40 subplotswere ( a 0.25 ha ( The plots for biometric measurement were established near the observation tower. We used 2.4 Biometric measurements Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (6) is the light transmission coefﬁcient of F in 2006, 2008, 2009, and 2012. Therefore, 11 Sasa ) was estimated by the combination of light in- (Sakata et al., 2010). We assumed that the pa- 2 tree − kg C m ) under different disturbance intensities were selected to mea- was assumed constant throughout the year and was estimated F , 2m ) × Pd / 0 2m Pd . t1 ln( is the PAR above the undergrowth and F 0 − AGB

= −

tree Six small plots ( Leaf area index of canopy tree (LAI The carbon content of stems, branches, and leaves was determined using an NC ana- The ratio of root to stem biomass used was 0.317 (Utsugi et al., 2007), and the carbon

sure the biomass and the leaf area index of 2001. by substituting values of PAR and LAI obtained by leaf litter measurements in 2000 and where Pd the canopy. The value of LAI within the canopy layer as follows: downward PAR was measuredquantum above sensor. Under the cloudy-sky forest conditions, Beer’s canopy Law and of the light penetration undergrowth was using applied the terception and the leaf litter measurements. For the light interception measurements, the ratio of carbon to biomass to be 0.5 for stem, branch, and leaf components. in previous reports (Smithwick et al., 2002; Lamlon and Savidge, 2003). We assumed the of leaves was 52.4, 48.5,values and were very 48.3 % near for the birch, 50 % oak, that and had castor been aralia, assumed respectively. as These the carbon content of biomass content of stems and branches was 48.9 % by dry weight for birch and oak, whereas that lyzer (Sumigraph NC-80, Shimizu, Kyoto, Japan) during destructive sampling. The carbon disturbance. and the carbon content in the soil were constant and equal before and after the windthrow content in the soilrameters used of was allometric equations 18 for biomass components, the ratio of root to stem biomass, (t1) and end (t2)AGB of a year. The aboveground net biomass increment (ANBI) is deﬁned as AGB is the aboveground biomass of living trees, and subscripts imply times at the beginning present study, and Ld is the stem and branch biomass of dead trees produced in a year. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Sasa during 1 − , at a rate 2 at each plot. day CO 2 − Sasa g C m was collected from a part undergrowth was buried in (SBM) were increased with Sasa Sasa Sasa uptake to and release from the forest, 2 were measured above CO 0 12 budgets after the disturbance are shown in Fig. 3. 2 ) and the biomass of ﬂux CO sasa , respectively. 2 1 − CO (LAI day 2 Pd) linearly (Utsugi et al., 2013; Mizoguchi et al., 2014b) and were − / Sasa . Maximum values of the monthly means of GPP, Re, and NEP were 0 1 − g C m day 2 − g C m

1.4

− The seasonal changes in the

The shapes of seasonal trends in GPP and Re after the disturbance were similar to the of 10.2, 4.7, and 6.0 respectively. During the defoliation period, the forest was a weak source of was observed from Maythe to positive and September negative and values a representing negative value from October to April, with peaked in June, decreasing gradually from mid-summer to autumn. A positive NEP value the snowy defoliation period from December to March. NEP increased rapidly in May and the snowy defoliation period.peaked in Re August, increased and after maintained snow an thaw almost with constant rising value air of temperature, 1.3 mid-August, and decreased gradually in autumn. GPP peaked in July and was 0 during and NEP before theare disturbance, shown represented in by Fig. the 2. monthly GPP means increased of after the bud daily burst, ﬂuxes, was almost constant from June to snowpack from mid-December to the beginning of April. Seasonal changes in GPP, Re, At the study site,all the leaves bud of burst canopy started trees at turned the yellow end during of October. April and the beginning of May, and

3.1 Seasonal changes in 3 Results

the transmittance (Pd estimated at all the subplots. The leaf area index of of the plot. Alldomly selected samples was were measured. dried Values and of weighed. Pd The area of 10 leaves that were ran- in the plot was separated into leaf and culm, and the root of the plots were inﬂuenced by the different light conditions. All aboveground biomass of Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 CO of ob- after the years years release) and was 2 CO uptake only occurred for and annual Re increased 2 1 − CO yr 2 − , respectively. In 2006, 2 Sasa g C m 1 − for 3 to 4 months after the disturbance as yr , 1.5 times greater than Re before the dis- 1 2 2 − 13 − CO day 2 g C m uptake) to a negative value ( − ﬂux 2 2 CO g C m CO budget was greatly altered by the disturbance. After the dis- , respectively, and they were 1.0 and 1.6 times greater, respec- 2 1 − CO (growth of surviving and recruiting trees), and Ld are shown in Fig. 5. day , being 6 % smaller and 39 % greater, respectively. The annual NEP y 2 1 . in 2010. NEP increased slightly under the forest restoration processes 1 − − ∆ 1 . The − yr 1 − 2 − yr day − yr g C m 2 2 2 − − − g C m

g C m g C m g C m

365 97 1.8 The carbon stocks are summarized in Table 1. For a 4-year period from 2000 to 2003, Changes in AGB, 3.3 Changes in biomass for canopy trees and − in 2011 and 2012. release in 2006 and 2007, which subsequently decreased gradually and bottomed out at − turbance, these ﬂuxes changedin year a after temporally year; heterogeneous Re and increased complicated gradually manner. and NEP GPP varied represented a weak to 1359 changed from a positive value ( disturbance, the annual GPP decreased to 1262 servations are shown indisturbance Fig. were 4. 1350, The 975, 4-year and average 375 annual GPP, Re, and NEP before the of observations are missing from September 2004 to June 2005; however, 2 servations were suspended because of the windthrow disturbance in 2004. Ten months Figure 4 shows interannual variation in GPP, Re, and NEP from 2000 to 2012. The ob- − 3.2 Interannual changes in

opposed to 5 months2 before months the in disturbance. 2012. In The particular, average NEP during the defoliation period from 2006 to 2008 was turbance. The disturbed forest absorbed tively, than those before theRe disturbance. from During the 2006 snowy to defoliation 2008 period, the was average 2.0 10.0 and 7.6 trends before the disturbance. Averaged maximum GPP and Re from 2006 to 2008 were Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (7) (8) (9) be- 1 − Pd), the yr / 2 0 − . SBM increased g C m 2 − , respectively (Oshima, (Sakata et al., 2010). We kg C m 2 Ld) hovered around 0, with − years is shown in Fig. 6 assuming − y ∆ kg C m Sasa . The small number of recruiting trees 1 − yr 2 , with a mean value of 140 − for Japanese white birch. However, the ANBI 1 − 14 y yr ∆ g C m 2 − , including leaf and branch biomass. The mean AGB of , g C m before the disturbance. This marginally positive value of , , 2 − 1 − 1717 3631 0598 . yr . . 2 − kg C m + 0 + 0 + 0 Pd Pd Pd / / / g C m 0 0 0 Pd Pd Pd × × × ranged from 92 to 164 039 709 244 . . . y , respectively. The total biomass change of ∆ = 1 = 0

= 0

increased and ranged from 92 to 197 Sasa Using the linear relation between the SBM and the light transmittance (Pd The

y that the turnovers of1961a, 1961b). culm, The mean leaf, SBM before and the disturbance root was 0.715 were 9, 3, and 3 of where SBMc, SBMl, and SBMr were the culm, leaf, and root (including rhizome) biomass SBMr SBMl SBMc three components of SBM were estimated as follows: in ANBI values before and after the disturbance were evident. larly and was greater in 2010 because of minor crown snow damage. No clear differences ∆ became countable after the disturbance. On the other hand, the mortality ﬂuctuated irregu- greater than that for Japanese white birch during the 4-year period. After the disturbance, dead-tree biomass (Ld) was greatervalue than for Japanese oak and that for the other surveyed species was positive and signiﬁcantly over the 4-year period, excluding 2001. This negative ANBI value demonstrated that the a mean value ofthe 17 mean ANBI was attributed to the negative ANBI of Japanese white birch that occurred fore the disturbance. The interannual value of ANBI (=

bance were the same as thatby before 40.4 the % disturbance. in After 2005 the and disturbance, had AGB decreased evidently stabilized by 2012. assumed that the ratio of root to stem biomass and the soil carbon content after the distur- AGB before the disturbance.biomass As (Utsugi shown et in al., Table 2007) 1, and the soil carbon root was biomass 18.0 was 31.7 % of stem Japanese white birch was 51.6 % and that of Japanese oak was 33.5 % of the mean total the mean AGB was 9.37 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (10) and the was mea- by the year 0 sasa 2 − kg C m ) were also estimated from sasa Sasa increased by a factor of 2.4 in the (LAI sasa reached 4.05 in 2007 and maintained Sasa sasa after 2005 fell to below a quarter of that before 15 ) and tree tree , we derived a linear correlation between LAI . with the turnover of leaves in mind. Because Pd was constant throughout a year and used a mean value of after the disturbance and reached 1.408 40 . Sasa F years + 1 years Pd / ) as calculated using Eq. (6) in 2000 and 2001 were 2.91 and 2.41, 0 F Pd × 71 , the maximum leaf area index of each year was estimated as the mean of .

after the disturbance. The value of LAI over the former 3 = 5 Sasa

sasa sasa Interannual changes in the maximum leaf area indexes are shown in Fig. 7, quoted from For years

and then, from 2007the to disturbance. 2012, it increased to a value of approximately 70 % of that before a constant value after. The total LAI of the forest just after the disturbance fell to about half, the disturbance. On the other3 hand, the value of LAI Mizoguchi et al. (2014b). The value of LAI LAI may not have been rigorously measured after the disturbance. sured at only one point near the observation tower, where the disturbance was more severe, LAI LAI transmittance as follows: 2.66 over all the years. For sion coefﬁcients ( respectively. We assumed the light transmittance quoted from Mizoguchi et al. (2014b). For the canopy, the transmis- The leaf area index for canopy tree (LAI 3.4 Changes in leaf area index for canopy trees and 2012. sharply during the ﬁrst 3 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | had Sasa Sasa sasa could continue to carry C increased by factors ◦ Sasa dropped by one sixth after the disturbance. reached a maximum during July or August, 16 tree tree increased by a factor of 2.4 after the disturbance sasa (41 % of the biomass before the disturbance) supplied to the 2 , which experienced a growth spurt, compensated for the GPP −

Sasa

kg C m

bris (CWD) of 4.82 of 1.50 and 1.61, as compared with that before the disturbance. The coarse-wood de- Figure 9 shows thefree exponential season. functions The between value air of temperature Re and after Re the in disturbance the at snow- 5 and 20

4.2 Relationship between monthly mean Re and air temperature a significant effect on GPP in the years immediately following the disturbance. value by the decline in canopythe trees in annual the GPP growing season. dropped Consequently, as by seen only in 6 Fig. % 4, after the disturbance. The increases in LAI The value of GPP for which was maintained until September (Mizoguchiabout et 70 al., % 2014b). by The 2007; total LAI nevertheless, recovered the to LAI only a small percentage. The value of LAI value after the disturbancetical was solid slightly lines. less Despite than the that forest before being the severely damaged, disturbance the in GPP the value ellip- decreased by (Fig. 7), the GPP value was small but clearly increased. In the growing season, the GPP elliptical dotted lines. Because LAI was not buried under snowThe during GPP November, value but after PAR was the very disturbance small was for greater photosynthesis. than that before the disturbance in the emerged from the snow pack and generally started photosynthesis in mid-April. The tional season (May and October).out In the photosynthesis leafless season, because only it is an evergreen species. The greater proportion of ing season (June–September), the leafless season (April and November), and the transi- Figure 8 shows anGPP anticlockwise in hysteresis the snow-free change season. in We could the separate relationship monthly data between into PAR three and groups: the grow-

4.1 Relationship between monthly mean GPP and PAR 4 Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C ◦ before the dis- 1 − yr 2 − g C m increase in the annual Re was 1 − yr 2 − . The fallen biomass decomposed into 1 − g C m yr 17 after the disturbance. Therefore, the mean decomposition source after the disturbance. Utsugi et al. (2010) indicated in 2006. The 380 1 2 years C (Fig. 9). In the snowy season, the value of Re was constant − ◦ . The annual Re increased from 978 yr CO 1 2 − − yr 2 − g C m in the ﬁrst 5 2 g C m −

kg C m

Carbon ﬂuxes measured by the two methods were in reasonable agreement with each Because the soil surface did not freeze and the soil temperature reached nearly 0

other. In general, the measurementsHowever, the by changes the before eddy and after covariance the method disturbance gave showed smaller the values. same tendency. Specif- Ra value of root wasof estimated Rs. as the remainder subtracted the value of Rh from the value were estimated by using incubation tests (T. Sakata, personal communication, 2010). The (Rh) of CWD was estimated in section 4.2. The Rh values of litter and soil decomposition (Ra) of aboveground parts(Utsugi et and al., soil 2008; Sakata respiration et (Rs) al., 2008; were Sakata estimated et al., by 2008). using The heterotrophic chambers respiration adding together ANPP and the changes in SBM and root biomass. Autotrophic respiration by the biometrical methods were integratedmeasured by into the Table 2 eddy and covariance method. were Net compared primary with production the (NPP) fluxes was calculated by The carbon balances within the SAP forest before and after the disturbance as estimated 4.3 Carbon balances before and after the disturbance over a period of 4 months and a considerable amount of Re was released. air temperature equal to 0 cover. The value of Re in the snowy season agreed with that in the snow-free season at an under the snow cover, most of the carbon was released as soil respiration through the snow extracting dead trees will have a significant effect on the change in Re after the disturbance. 2.1 times as largematter as may constitute the half decomposition of the rate increased of annual Re. CWD. The The forest decomposition management policy of of soil not organic turbance to 1359 0.916 rate was 183 that the decomposition rate of CWD is 0.04 forest floor resulted in a Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | %, re- had 2 30 > CO release. 2 Sasa CO after the disturbance, with release increased steadily and years 2 CO caused a gentle increase in , greater than the growth rate of trees shown 18 1 Sasa − . Because the carbon budget changed drastically yr 2 − years became saturated, g C m and the light at the forest floor resulted in a compensatory sasa were limited by the availability of light above the undergrowth rapidly grew during the first 3 sasa sasa Sasa , respectively. Because about 80 % of the fallen CWD remained in 1 − yr 2 − fluxes measured by the eddy covariance method were summarized in Table 3. g C m 2

Because SBM and LAI The Ra of the canopy trees decreased drastically, but the increased Ra of

ments from a period longer than 10 age were also included. The measurementsturbances that were included taken periods at both eight before sites. and Only after two dis- sites (sites TSE and SAP) included measure- events, harvest, tree thinning, and plantation. Some mature forests with an identiﬁed stand Data at 75 sites wereage selected of with a a mature focus forest. on The the disturbances history included of forest a ﬁres, disturbed insect forest infestation, and windthrow a stand The 4.4 Comparison with other disturbed and mature forest ecosystems

stabilized in 2010. Becauselease the decreased recruitment slightly of under forest trees restoration. increased in 2012 (Fig. 5b), Therefore, after SBM and LAI slight decrease in the annualin GPP. NEP Fig. values 4, in because 2006 and a 2007 remarkable were growth constant, of as shown in Fig. 5. Increases in LAI in 2008 (Figs. 6 anda 7), maximum growth rate of 213

plays an important role in the carbon balance in the forest. the annual Re after therate disturbance, of as CWD shown was in increasing year Fig. by 4, year. suggested The that change the in the decomposition Rh value after the disturbance 2009, CWD continued to decompose for long periods. A steady increase in the value of increases in the decomposition ofand CWD 190 and soil organic matter were estimated to be 183 other hand, the value of Rh was increased by a factor of 1.9 after the disturbance. The a compensatory effect. After the disturbance, a slight reduction in Ra occurred. On the and NEP changed from a positive value to a negative value. ically, GPP decreased by only a few percentage points, Re increased at a rate of Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | uptake 2 Re plotted CO / Re in this case was / except for Norunda, De 1 > (data before disturbance) is 0 ≤ Re) in the forest is shown in Table 3 / Re changed with the type and intensity / Re with years greater than or equal to 100 / 19 Re with years / Re for the forests were / , as mentioned above, will surely affect the carbon balance. We Sasa Re at the SAP site with that at the TSE site, where trees were clear-cut / uptake occurred in the forest ecosystem after a long period and in most of 2 Re after the disturbance changed rapidly and widely, as shown in Fig. 10. At / CO Re dropped gently at the SAP site. The management procedure adopted after /

The GPP The calculation of carbon uptake efﬁciency (GPP

and half the biomass was removed as logs (Aguilos et al., 2014). The ecosystem carbon compared the GPP role in the distribution ofa remarkable decomposable growth organic of matter. An increase in Rh from CWD and the disturbance at the SAP site, where all dead trees remained on site, played an important most disturbed sites, the greatestthe decreases GPP appeared just after the disturbance, whereas 1.46, demonstrating a considerable carbon sink. the mature or olderby forests. an For unmanaged example, 250-year-old Knohl forest et in al. central (2003) Germany. showed The a GPP large in Fig. 10, (Carrara et al., 2003).where there The was cause a burnt of forest the as reported carbon by Mkhabela source et in al. (2009), F77, is Saskatchewan, unknown. As Canada, show De Inslag in Belgium was losing carbon as a result of intensive thinning during the 1980s unusual carbon balance (Lagergren etcarbon al., 2008). is Valentini being et al. lost (2000) in pointed Norunda out as that the a result of past soil drainage, plowing and fertilization. Inslag, and F77 listed in Table 3. Norunda, in central Sweden, has been shown to have an the right margin in Fig. 10. The GPP on the left marginmature was forest greater before than the 1 (carbon disturbance. sink), The and mature all or values older were forests derived are from also the expressed on of the disturbance, they were scattered around the line equal to 1. The GPP plotted on the leftis margin. plotted Similarly, the on GPP the right margin. Because the GPP the mature forest in Fig. 10. The GPP and plotted with years since the last disturbance for the disturbed forest or stand age for term. in the years after the disturbance, it is very important to maintain measurements over a long Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | at all disturbed increased rapidly, years Sasa at the SAP site. The greater residual years 20 thereafter in a deciduous broadleaf forest in years Re crosses the compensation point after approximately / compared with over 10 years Re crosses the compensation point after approximately 20 / at the SAP site.

years We characterized the SAP site by the impact caused by the windthrow and the sub-

budget of forest management as well as the disturbance type. When comparing the carboning uptake sites efficiency with at various the kinds SAP of site disturbances, we with emphasized that the at importance others, to includ- the carbon dead stands remaining at the study site, strongly affected the carbon budget over the years. periods before and after the disturbance. The forest management, which resulted in the sequent forest management adapteddamaged after by the windthrow disturbance. are novel. The In observations particular, of the a measurements forest reported here include Consequently, the carbon balance afterand the the disturbance decomposition was of residues. controlled by the new growth bance suggested that the decomposition rate of the CWD was increasing year after year. the disturbance. On the otherthe hand, decomposition the of annual residual Re CWD. increased A by steady 39 %, increase mainly in because the of annual Re after the distur- ultimately contributing to the total GPP. The annual GPP only decreased by 6 % just after tensity at the forest floor after the disturbance, the photosynthesis of Hokkaido, Japan. Before thesink, disturbance, and the it forest changed to fulfilled a the carbon source role after of the disturbance. an Because evident of increased carbon light in- windthrow disturbance and over 8 We performed measurements of the carbon balance over a 4-year period before the 5 Conclusions

sites. We estimate that the15 GPP the GPP CWD at the SAP site resultedplays in an later important restoration. Consequently, role the in amount of the the disturbance residues chronosequences. Figure 10 demonstrates that TSE site was after 8 compensation point at which carbon balance changed from a carbon source to a sink at the Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | above years and water vapour fluxes for 2 2 CO 21 K. Yamanoi and Y. Mizoguchi designed and carried out the meteorological This study was supported in part by Research Revolution 2002 (FY ence carbon dioxide fluxesMeteorol., of 148, black 537–548, spruce 2008. ecosystems in eastern North America?, Agr. Forest dioxide fluxes after disturbancedoi:10.1029/2010JG001390, 2010. in forests of North America, J.Euroflux forest Geophys. site, Res., Agr. Forest 115, Meteorol., 108, G00K02, 181–197, 2001. Davis, K. J., Desai,Kolb, A. T. E., R., Lavigne, Dore, M. S.,Montes-Helu, B., Engel, Law, M., V., B. Fuentes, Noormets, E., J. Margolis, A., D., H. Goldstein, Randerson, A., A. Martin, J. H., T., T., McCaughey, Goulden, J. Starr, H., M. G., Misson, L., L., and Xiao, J.: Ecosystem carbon recovering from a2014. clear-cutting in a cool-temperate forest, Agr. Forest Meteorol., 197, 26–39, Fukazawa, T., Takahashi, H., Kotsuka,hashi, C., Y., Sakai, Murayama, R., T., Ito, Saigusa, K., N., Watanabe, and Y., Fujinuma, Sasa, Y., K.: Taka- Dynamics of ecosystem carbon balance Bergeron, O., Margolis, H. A., Coursolle, C., and Giasson, M.-A.: How does forest harvest influ- Berbigier, P., Bonnefond, J.-M., and Mellmann, P.: Amiro, B. D., Barr, A. G., Barr, J. G., Black, T. A., Bracho, R., Brown, M., Chen, J., Clark, K. L., Aguilos, M., Takagi, K., Liang, N., Ueyama, M., Fukuzawa, K., Nomura, M., Kishida, O., Y. Ohtani, Y. Nakai, S. Suzuki, S. Yuta, H. Sugata, and H. Yamamoto, for theirReferences research assistance. Ministry of the Environment. Wecarbon are to grateful S. to Kuramoto T. Sakata for for offering personal litterfall communication data. regarding We soil also wish to thank our colleagues, K. Kitamura, and Fisheries; and the Global Environment Research Account (FY 2007–2014) from the Japanese Japanese Ministry of Education,Fund (Environment Culture, Research: Sports, FY Science 2006–2014) and from Technology; the the Japanese Ministry Project of Research Agriculture, Forestry 2002–2007) and Grants-in-Aid for Scientific Research (19 380 095 and 19 587 019) from the Acknowledgements. experiments. H. Utsugi designedYamanoi the prepared biometrical the manuscript experiments, with and contributions all from authors coauthors. carried them out. K. Author contributions. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , Agr. Forest Meteorol., 119, years 22 exchange of mixed forest in Belgium over 5 2 CO ica, J. Geophys. Res., 117, G02022, doi:10.1029/2011JG001733, 2012. 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M., Wirth, C., Rebmann, C., Lühker, B., Mund, M., Knohl, A., Schulze, E.-D.: Biological control of the terrestrial carbon sink, Biogeosciences, 3, 147–166, Sano, T., Hirano, T., Liang, N., Hirata, R., and Fujinuma, Y.: Carbon dioxide exchange of a larch Sakata, T., Utsugi, H., and Aizawa, S.: Soil Sakata, T., Utsugi, H., Sakai, H., Ishizuka, S., and Tanaka, N.: Estimation of Saigusa, N., Yamanoto, S., Murayama, S., and Kondo, H.: Inter-annual variability of carbon budget Pilegaard, K., Hummelshøj, P., Jensen, N. O., and Chen, Z.: Two years of continuous Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | period after years exchange on timescales from hourly to 2 CO 28 in northern Japan, Trans. Mtg. Hokkaido Br. Jpn. For. Soc., years and branch decomposition in18th typhoon boreal in deciduous 2004, forest Trans. Mtg. of Hokkaido Br. northern Jpn. Japan For. Soc., – 58, 4 83–86, 2010 (in Japanese). abe, T.: Relation between intensityTrans. 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O., Pilegaard, K., Lindroth, A., Grelle, A., Bernhofer, C., Grunwald, T., Aubi- of biomass production of Sasa in boreal deciduous forest of northern Japan – 8 Yasuda, Y., Saito, T., Hoshino, D., Ono, K., Ohtani, Y., Mizoguchi, Y., and Morisawa, T.: Carbon bal- Yasuda, Y., Watanabe, T., Ohtani, Y., Okano, M., and Nakayama, K.: Seasonal variation of Yasuda, Y. and Watanabe, T.: Comparative measurements of Welp, L. R., Randerson, J. T., and Liu, H. P.: Seasonal exchange of Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements for density effects Vickers, D. and Mahrt, L.: Quality control and flux sampling problems for tower and air craft data, J. Valentini, R., Matteucci, G., Dolman, A. J., Schulze, E. D., Rebmann, C., Moors, E. J., Granier, A., Utsugi, H., Harayama, H., Kitaoka, S., Uemura, A., Mizoguchi, Y., and Yamanoi, K.: The estimation Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 18. 18. 2.37 1.39 Soil carbon is quoted from Sakata 2 30 ) Before disturbance After disturbance 2 − kg C m 1 2 biomass 0.72 1.20 StemBranchLeaf 7.47 1.73 0.17 4.39 1.12 0.10 Root biomass is 31.7 % of stem biomass (Utsugi et al., 2007). Sasa Soil carbon Carbon stock ( Aboveground biomass of living treesRoot biomass 9.37 5.61 Carbon stocks at the SAP site before and after the windthrow disturbance. The periods 1 et al. (2010). before and after the disturbance are 2000–2003 and 2006–2008, respectively. Table 1. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 131 − and root biomass. Autotrophic 123 − Sasa 31 267 374 15521285 1349 978 1517 1641 1293 1424 1 1 Ra) 1 Rh) + ) Biometric Eddy cov. Biometric Eddy cov. − 1 Rh) − + yr NPP NPP 2 Ra − = = = g C m Mean annual rates were measured by the eddy covariance method and were calculated NEP ( GPP ( NPPRe ( RaRhRs 678 875 410 730 660 858 783 984 Component( Before disturbance After disturbance 1 biometrically by the formula. Carbon balances at the SAP site before and after the windthrow disturbance. Gross primary respectively. Sakata et al., 2008) The periods before and after the disturbance are 2000–2003 and 2006–2008, values of litter and soil decompositioncommunication, were 2010). estimated by The using value incubation tests of (T. Sakata, Rs personal was estimated by using chambers (Sakata et al., 2008; root was estimatedrespiration as (Rs). the The remainder Rh subtracted value the of heterotrophic coarse-wood respiration debris (Rh) was from estimated the in soil the section 4.2. The Rh of aboveground parts were estimated by using chambers (Utsugi et al., 2008). The Ra value of the aboveground net primaryrespiration production (Ra) is and composed the of respirations changes from in leaves,branches, stems, and roots. The Ra values by eddy covariance methods. Net primary production (NPP) was calculated by adding together Table 2. production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) were measured Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.84 GPP/Re References ) 3 1 4378 1.01, 0.91 Mkhabela et al. (2009) 0.95, 0.92 52 0.88, 0.94, 0.95 Mathys et al. (2013) − 128 , 34 0.98,1.09 123 0.36, 0.46 124 0.62, 0.74 129 1.19, 0.88, 0.84 606 0.90, 0.41 − − − 7 , 11456, 4 0.84, 0.94, 0.89, 0.94 Brown et 0.82, al. 1.35 (2010) Welp et al. (2006) yr − , − − − − NEP 2 − , , − , 41 39 − 57, − − − 155 167 133 103, 33, , − − − − − g C m , 108 82 − − )( 3 1 − Re yr 2 − g C m )( 3 32 1 − 1034 924 110 1.12 Desai et al. (2005) yr GPP 2 − g C m 2 300 > history ( 1 MXFMXF Insect Insect 0, 1, 2 0, 1 877, 804, 702 1370, 1170 740, 907, 831 137, 1187, 1153 183, 17 1.15, 1.01 ENF Mature ca. 80 499 426 70 1.16 Characteristics of the eddy covariance measurement in forest sites. Sites were selected -1930, -1850HBS00 ENF FireMS ENFMRP, Harvest–scarf–plantPB,YRP, ENFYHW 4, 5 Harvest–mature 75, 154 ENF Plant–thin–mature ENF ENF ca. 90 DBF Fire 274, Harvest 359 630, 720 Harvest 63 440, 483 1360 490, 667 1153 8 12 3 140, 52 989 1059 514 673 697 1.29, 1.08 371 648 739 470 827 1.38 313 2.24 195 1.43 1.43 HDF88, HDF00 ENFF89, Harvest–burn–plantF77,OJP,HJP02, 14, 3HJP94, ENFHJP75 ENF Fire ENF ENF Fire 1214, 435 ENF-1981, -1964, Fire–mature Harvest ENF Harvest ENF Harvest 1347, Fire 1041 88,89 15, 16 27, 28 2, 10, 3 11 29, 30 560, 594 903, 902 23, 40 752, 906 353, 410 89, 99 544, 592 556, 558 787, 849 710, 640 791, 984 360, 376 245, 222 464, 513 4, 115, 36 580, 53 478 80, 79 1.01, 131, 1.15, 1.06 62 1.06 1.17, 1.15 1.23, 1.34 UCI-1998, -1989, ENF Fire 5, 15 380, 450 443, 446 63, 4.5 0.86, 1.01 MA, USA, Harvard ForestNJ, USA, Pine Barrens MXF Windthrow–Mature MXF 75–110 Insect 1400 0, 1 1150 1153, 491 1007, 785 242 146, 294 1.22 Urbanski et 1.14, al. 0.63 (2007) Clark et al. (2010) MI, USA, SylvaniaMI, USA, UMBSOH, USA, Toledo DBF Mature MXF DBF Harvest–burn Mature 85 45 1400 1148 1240 845 160 303 1.13 Gough et al. (2008) 1.36 Noormets et al. (2008) OR, USA, YS,WI, USA, Willow CreekWI, USA, MHW, DBF ENF Insect Harvest DBFWI, USA, Willow Creek Mature DBF mature 0, 1, 23, 2 24 1099, 898, 1202 65 704, 809 776, ca. 821, 70 778 323, 77, 422 659, 696 1047 1149 1.42, 1.09, 1.54 Cook et al. (2008) 45, 113 387 686 1.07, 1.16 Schwarz et al. (2004) 655 464 2.71 Noormets et al. (2007) 1.68 Desai et al. (2005) QC, Canada, EOBS, ENF Fire ca. 100 592 586 6 1.01 Bergeron et al. (2008) SK, Canada, F98, ENF FireMB, Canada, 6, 7 388, 456 385, 499 3, Goulden et al. (2011) BC, Canada, MPB-06, -03BC, Canada, MPB-09 ENFBC, Canada, DF49 Insect ENF Insect–harvest ENF, Harvest–burn 1, 1, 2, 2, 4, 3 5 439, 522, 432, 522 521, 812, 555, 954, 53 488, 922 518 920, 1011, 974 1991 1737 254 1.15 Humphreys et al. (2006) Site locationname or symbolNorth America AL, USA, Poker FlatAL, USA Delta Junction type Forest Disturbance ENF ENF Fire Fire Years 3, 15 5 193, 436 299 234, 322 229 70 1.31 Iwata et al. (2011) were added. with a focus on disturbance or management history. Some mature forest sites of a certain stand age Table 3. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Some 3 0.95 Lagergren et al. (2008) 0.90 0.93 Carrara et al. (2004) 0.64 0.50 Knohl et al. (2002) GPP/Re References Years since last disturbance or stand age. 2 ) 3 1 52 91 5145 1.12, 0.92 0.78, 0.88 − 112 427 109 365 1.38, 0.77–0.94 This study 591 0.64–0.82 Hirano et al. (2012) 882 0.36, 0.63 Clark et al. (2004) − − − − yr − − − − − , − NEP 2 , 569–52 1.03, 0.46–1.05 Aguilos et al. (2014) 13–172 1.16, 0.99–1.11 Misson et al. (2005) − to 109 − − − 82 to 1269 318 − − g C m − )( 3 1 − Re yr 2 − g C m )( 3 1 − 879 786 110 1.12 Dore et al. (2010) 3243 3119 124 1.04 Kosugi et al. (2008) yr 33 GPP 2 − g C m 2 100 100 > > history ( 1 DBF Coppice 2 1420 2220 ENFENF Harvest–plant Harvest–plant 10, 11 24, 25 2922, 2605 2695, 2517ENF 2346, 2002 Harvest–plant 1956, 1907 3 576, 603 741, 610 1.25, 1.30 1.38, 1.32 988 1100 ENFGS Thin Fire 0, 1 10, 11 909, 826 372, 401 811, 902 480, 453 118, are averaged. years Continued. Sapporo, Japan, SAPTomakomai, Japan, TMKAppi, Japan, APIKawagoe, Japan, KWGFujiyoshida, Japan, FJY DNF DBFTakayama, Japan, TKYKiryu, Windthrow–plant Japan, KEW WindthrowPasoh, Malaysia, DBF PSOKalimantan, ENF Indonesia, DB DBF Coppice–insect 48 DBF Coppice–mature 0, Harvest–mature 2–8 ca. Mature 25 BS ca. 1349, 90 1214–1460 EBF ENF ca. 90 975, 1360–1741 Mature Drain–fire Plant 374, 1673 ca. 50 1453 1802 1177 2–6 1461 43 1071–1428 978 1190 1413 899 1662–1871 1539 212 742 263 388 278 1.15 1060 Hirata et al. (2007) 1.22 1.28 237 Yasuda et al. Mizoguchi (1998) 1.31 et al. (2012) Yasuda et al. (2012) 523 1.32 Saigusa et al. (2005) 1.45 Takanashi et al. (2005) Mongonmorit, Mongolia, SKTGwangneung, Korea, GDKTeshio, Japan, DNF TSE Thin–fire–insect DBF 70–150 Mature MXF Harvest–plant 80–200 525 0, 1–9 1439, 481–1238 1395, 1035–1229 835 440 44, 746 85 1.19 87 Li et al. (2005) 1.12 Kwon et al. (2009) Eisenach, Germany, HainichBrasschaat, Belgium, De InslagHesse, France, FR02 DBF MXFBordeaux, France, BrayLes Coppice–mature Plant–thin Landes, France, BilosCentral ca. Italy 250 DBF ENFAsia ENF Mature–thin Plant Harvest 71 1560 DBF 30 Coppice–mature 1234 2 28 1068 10 1128 1326 2255 727 492 1600 891 1680 996 1.46 Knohl 1160 et al. (2003) 238 575 290 381 1.27 Granier et al. (2000) 1.34 0.73 Berbigier et al. (2001) Kowalski 1.38 et al. (2003) Kowalski et al. (2004) Central Sweden, NorundaZealand, Denmark, SorøOxford, UK, Wytham WoodsUK ENF DBF DBF Harvest–drain Coppice–mature Mature 50–100 40 1075 80 ENF 2110 Harvest–mature 1127 1303 41 1980 1120 1970 130 1385 184 1.07 Thomas et al. (2011) 1.16 496 Pilegaard et al. (2001) 1.42 Kowalski et al. (2004) CA, USA, BlodgettFL, USA, GainesvilleEurope European Russia, Tver ENF ENFHyytiälä, Finland, SMEAR II Plant–thin Harvest–plant ENF MXF Plant 1, 2 0, Windthrow 1–3 1462, 1260–1777 1261, 1254–1604 705, 1504 201, 2 36 1974, 2386 109 949 218 720 228 1.32 Markkanen et al. (2001) name or symbolNC, USA, Duke ForestAZ, USA, Flagstaff ENF type Plant MXF Mature 17 1808 1203 605 1.50 Lai et al. (2002) Site location Forest Disturbance Years DBF: deciduous broadleaf forest; DNF: deciduous needle forest; ENF: evergreen needle forest; EBF: evergreen broadleaf forest; MXF: mixed forest; GS: grasses and shrub. data older than 30 1 Table 3. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 34 Southeast-facing aspect at a deciduous broadleaf forest in Sapporo, Japan. This forest Figure 1. was disturbed by strong wind in September 2004. The picture was taken on 12 May 2005. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). 1 − day 2 − g C m 35 Seasonal variations in gross primary production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) beforesent the 4-year disturbance monthly between means 2000 and and standard 2003. deviations The of fluxes daily repre- values ( Figure 2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 36 Seasonal and interannual variations in gross primary production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) after the disturbance between 2006 and 2012. Figure 3. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 37 Interannual carbon flux changes in gross primary production (GPP), ecosystem respiration annual sums are missing in 2004 and 2005. (Re), and net ecosystem production (NEP) before and after the disturbance. The values for the Figure 4. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | aboveground (b) stem and branch biomass of dead (c) ), and y ∆ 38 of surviving trees from 2000 to 2004 include the recruiting y aboveground biomass of living trees (AGB), ∆ (a) Interannual changes in trees. trees produced in a year (Ld). The Figure 5. biomass increment of surviving and recruiting trees ( Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). S. senanensis and Sasa kurilensis 39 Interannual changes in carbon stock in dwarf bamboo ( biomass is estimated from the light transmittance. Sasa Figure 6. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 40 ). Each of them is estimated from the light transmittance. S. senanensis and Interannual changes in maximum leaf area index in the canopy tree and dwarf bamboo Sasa kurilensis ( Figure 7. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 41 Relationships between monthly mean gross primary production (GPP) and monthly mean dotted lines indicate theand growing leafless season season (June–September), without transition snow season (April (May and and November), October), respectively. spectively. The snow-free season is separated into three periods. The elliptical solid, broken, and photosynthetically active radiation (PAR) inby the snow-free ellipses. season. Black Each and month’s data white are circles enclosed represent monthly data before and after the disturbance, re- Figure 8. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 42 . The broken line indicates the regression equation after the disturbance, . 10 10 / / Ta Ta 02 93 . . 2 1 × × 94 33 . . Relationships between monthly mean ecosystem respiration (Re) and mean air temper- = 1 = 1 i.e., Re disturbance, respectively. The solidi.e., line Re indicates the regression equation before the disturbance, ature (Ta) in the snow-free season. Black and white circles represent values before and after the Figure 9. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . years (data before disturbance) is 0 ≤ 43 are averaged. In particular, data of the TSE site (Aguilos years The carbon uptake efficiency (GPP/Re) in forest with years since last disturbance in the et al., 2014) and SAPinclude periods site both (the before present and study) after are the indicated. disturbance At and were these taken two for sites, over the 10 measurements the right margin. Data older than 20 forest or stand ageplotted for on the the mature left forest. margin. Similarly, The the GPP/Re GPP/Re with with years years older than or equal to 100 are plotted on Figure 10.