Mohan KC 1,2 · Euan G. Mason 1 · Horacio E. Bown 3

Abstract Silvicultural practices applied in managed forest plantations may help counteract the ef fects of climate change by inf luencing soil surface CO 2 ef flux ( F s ). Understanding the ef fects of silvicultural practices on F s will provide unbiased estimates of carbon f luxes and allow better silvicultural decisions for carbon sequestration. Therefore,we assessed how F s dif fered seasonally across silvicultural practices (i.e., stocking levels, clone, fertilization and weed control treatments) and evaluated the ef fects of soil temperature ( T s ) and soil volumetric water content ( θ v ) on F s across these practices for a mid-rotation (14 year-old) Pinus radiata plantation in the Canterbury region of New Zealand. There were signif icant dif ferences in F s ( p < 0.05) over the four seasons, three levels of stocking, and f ive clones. The ef fects of fertilization and weed control applied 12 years previously on F s were insignif icant. Annual estimate of F s (mean ± 1 standard deviation) from the study site was 22.7 ± 7.1 t ha −1 a −1 in the form of CO 2 (6.2 ± 2.1 t ha −1 a −1 in the form of C).F s values were consistently higher in plots with 1250 stems ha −1 compared to 2500 stems ha −1 , which may be related to a strong soil resource limitation because of the close spacing in the latter plantation. Signif icant dif ferences in F s across clones suggest that variations in carbon partitioning might explain their growth performance. Silvicultural treatments inf luenced F s response to soil temperature ( p < 0.05), resulting in models explaining 28–49% of the total variance in F s . These f indings provide insights into how silvicultural management decisions may impact F s in mid-rotation radiata pine plantations, contributing towards developing more precise and unbiased plantation carbon budgets.

Keywords Clone · Silvicultural practices · Soil CO 2 ef flux · Stocking · Weed control

Introduction

Forests store some 75% of all carbon in terrestrial ecosystems accounting for up to 40% of carbon exchange between the biosphere and the atmosphere (Raich and Schlesinger 1992). Soil CO2ef flux is the second largest f lux in the global carbon cycle, which is a magnitude greater than emissions from the burning of fossil fuel (Raich and Schlesinger 1992).Soil CO2ef flux changes due to anthropogenic factors may therefore accelerate global warming by speeding up global carbon cycling (Raich and Potter 1995; Schlesinger and Andrews 2000). For example, land clearing and utilization,and deforestation increases soil CO2ef flux as a result of increased rates of decomposition (Rapp 2014). Given the extent of global forest cover, minor changes in disturbance regimes and forest management practices may considerably af fect soil carbon f luxes (Maier and Kress 2000).

Radiata pine(Pinus radiataD. Don) plantations occupy more than four million hectares worldwide (Mead 2013),exhibiting greater productivity and plasticity than many other tree species. In New Zealand, radiata pine is the predominantly planted species, accounting for about 90% of 1.73 million ha (NZFOA 2019). Intensively managed plantations represent an important pool in the global carbon cycle(Templeton et al. 2015). The productivity of radiata pine plantations can be greatly altered by silvicultural management practices (Hollinger et al. 1993). In intensively managed plantations, these practices may contribute to counteract the ef fects of climate change. Total soil surface CO2ef flux (Fs) consists of two parts (Tyree et al. 2014): (1)autotrophic respiration, which is root respiration resulting from maintenance, growth and ion uptake; and, (2) heterotrophic respiration from the decomposition of soil organic matter by micro and macro fauna. Environmental factors signif icantly inf luence forest productivity and decomposition of soil organic matter, explaining seasonal variation inFs(Schlesinger and Andrews 2000). For example,Fswas higher in summer and lower in winter in North Florida’s slash pine (Pinus elliottiiEngelm) plantation, corresponding to changes in ambient temperatures and soil moisture (Ewel et al. 1987).

Fertilization, weed control, planting at dif ferent stocking levels and with dif ferent genotypes are common silvicultural practices for radiata pine plantations throughout New Zealand (Mason and Milne 1999). The purpose of these practices is to produce healthy and vigorous trees by enhancing growth and productivity (Mason 1992). A previous study indicated that silvicultural practices have long term impacts onFsin intensively managed plantations (Tyree et al. 2006).These practices can signif icantly inf luenceFsby altering the microclimate of the site, including light, soil moisture (θv),soil temperature (Ts), and the soil microbial community. For example, fertilization has been shown to decrease (Samuelson et al. 2004), be independent of (Tyree et al. 2006; Templeton et al. 2015), and increase (Bracho et al. 2018)Fsin loblolly pine (Pinus taedaL.) plantations. Moreover, two contrasting loblolly pine clones dif fered in theirFsresponses to nutrient manipulations in terms of both partitioning and physiology (Tyree et al. 2009). Furthermore, stocking levels signif icantly af fected both heterotrophic and autotrophic soil CO2ef flux in lodgepole pine (Pinus contortaDougl.) (Litton et al. 2003a).

The main research topics for radiata pine plantations in New Zealand are silviculture practices, genetics (Mason and Kirongo 1999; Lasserre et al. 2005; Mason 2008), growth and yield modelling, fertilization, and weed control practices(Mason et al. 1996; Mason and Milne 1999), and carbon cycling and partitioning (KC et al. 2020). However, understanding how these practices af fect the dynamics ofFsin radiata pine plantations is limited. Therefore, the objectives of this study were: (a) to assess the inf luence of stocking,fertilization, weed control, and clone selection onFs; and,(b) to determine the inf luence of soil temperature and soil volumetric water onFsacross silvicultural treatments in a young radiata pine plantation. It was hypothesized that: (1)Fswould increase with stocking; (2) faster growing clones would exhibit greaterFs; (3)Fswould be independent of fertilization carried out 12 years before; (4)Fswould be independent of weed control carried out 12 years before; and,(5) bothTsandθvwould explain most of the variations inFsacross the silvicultural treatments. This study will contribute to better understanding of dif ferences among silvicultural management decisions onFswhen developing stand-level carbon budget models in forest plantations.

Materials and methods

Study site and experiment

The experiment was located in Rolleston, Canterbury, New Zealand (43° 37.2′ S and 172° 20.4′ E) (Fig. 1 a). It was established by the School of Forestry, University of Canterbury on land owned by the Selwyn District Council,comprising 7.5 ha of radiata pine planted in 2005. The site is approximately 45 m a.s.l. on a plain (Fig. 1 a). Typical summer daytime maximum temperatures range from 18 to 26 °C (Fig. 1 b), but may rise above 30 °C. Winters have daytime maximum temperatures from 7 to 14 °C (Salekin et al. 2019; NIWA 2020) (Fig. 1 b). Mean annual rainfall is approximately 618 mm with a monthly range of 38 to 68 mm (NIWA 2020) (Fig. 1 b). Northeasterly winds occur most frequently in coastal sites throughout the year while southwesterly winds are more frequent during winter (NIWA 2020). The site had formerly been livestock pasture. The soil is a Lismore stony silt loam with aggradation gravel as a parent material and also includes partial glacial gravel (Rennie and Bennett 1981 ; Hewitt 2010).

The experimental design consisted of 48 permanent plots with a randomized complete block factorial split plot with four complete blocks (Mason 2008), with an arrangement of factors within each block. Plots 1–12, 13–24, 25–36,and 37–48 corresponded to blocks one, two, three, and four respectively (Fig. 1 c). The main plots consisted of three levels of stocking (625, 1250 and 2500 stems ha−1). A f irst split consisted of four levels of follow-up weed control and fertilization treatments (fertilization, F; herbicide, H; both,FH; and no chemicals). Fertilization was carried out once in year 1 and once in year 3 (Nitrogen, Phosphorus, Potassium,Sulphur, and trace elements at a rate of 80 g per tree). Strip weed control was applied in years 1 and 2, and a follow-up herbicide treatment with complete clearance in year 3 and in subsequent years when required. A second split consisted of f ive dif ferent clones randomly allocated to all plots, with 1,2, 3, 4 and 5 indicating dif ferent clonal genotypes (Mason 2008). Measurements of soil surface CO2ef flux rates (Fs)were carried out when the plantation was 14 years-old,12 years after the last fertilization and herbicide applications were performed.

Fig. 1 Location ( a), ombrothermic diagram–January–December 2017 ( b) and layout of the experimental trial ( c)

Measurement of soil surface CO 2 ef flux

Ef flux rates (Fs) were measured using an infrared gas analyzer (EGM-4, PP Systems, Hitchin, Hertfordshire, UK)equipped with a soil respiration chamber (SRC-1) with a 10- cm inner diameter. Two hundred and forty PVC collars(10 cm wide × 6 cm high) were placed into the soil and left undisturbed for one year beforeFsmeasurements were made.Fswas measured at the centre within the two rows for each clone in each plot. Nine hundred and sixty measurements were made (48 plots × 5 clones × 4 seasons). Measurements were carried out between 9:00 AM and 4:00 PM during autumn (13–16 April 2017), winter (7–10 July 2017), spring(3–6 October 2017), and summer (13–16 January 2018).

Measurement of soil temperature and soil water content

Soil temperature (Ts) and soil volumetric water (θv) were measured simultaneously toFs, within 10 cm of the PVC collar.Tsvalues were determined using a built-in temperature probe (STP-1) of the EGM-4 at a 10-cm soil depth.Theθvwas measured with a portable moisture meter SM150T (Delta-T Devices Ltd., Burwell, Cambridge,UK), at 10 cm. Measurements of the SM150T were calibrated using samples analyzed by a gravimetric method consisting of oven drying soil samples of a known volume(Walker et al. 2004).

Scaling to annual soil surface CO 2 ef flux

Fsvalues were scaled into t ha−1a−1in the form of CO2using the exponential equations ofFsvs Tsandθvdeveloped for this experiment (Eq. 4) and continuous measurements ofTsandθvrecorded by in-site micrometeorological stations.

Statistical analysis

The inf luence of stocking, specif ic clone, fertilization, weed control, and season onFs,Ts, andθvwere examined using linear mixed ef fects models of thenlmepackage in R statistical software (R Core Team 2018), considering blocks as random ef fects. Fixed ef fects consisted of stocking, clone, fertilization,and weed control and their two-way interactions. A mathematical representation of the linear mixed-ef fects model in matrix form is given in Eq. ( 1) (Zuur et al. 2009).

whereYiis the response variable (Fs,Ts, andθv) for dif ferent treatment levels i (i.e., three levels of stocking, two levels of fertilization, two levels of weed control, and f ive levels of type of clone),Xi×is the f ixed term,Zi×biis the random term, andiis error term.

To determine the inf luence ofTsandθvonFsacross silvicultural treatments, the following commonly used exponential functions were tested:Ts-based model [Eq. ( 2)] (Lloyd and Taylor 1994), and the combinedTsandθv-based model[Eq. ( 4)] (Lavigne et al. 2004). Temperature sensitivity (Q10),i.e., the response ofFsto a 10 °C change inTsvalues, was estimated across all silvicultural treatments using Eq. ( 3) based on the model of Lloyd and Taylor ( 1994). Fitted models were evaluated using two of the most commonly used goodness-off it statistics (Huber-Carol et al. 2012): the root mean square error (RMSE), and the coefficient of determination (R2).Regression models were f itted in the R statistical software (R Core Team 2018).

Results

Inf luence of T s and θ v on F s across silvicultural treatments

For the period of the experiment,Tswas strongly controlled by the season (F3,889= 9677,p< 0.001), and specif ic clone(F4,889= 9.37,p< 0.001) (Table 1). Stocking, fertilization,and follow-up herbicide treatments had no signif icant ef fects onTs(p> 0.05). When examined by season,Tswas signif icantly inf luenced by the main clonal ef fect in all seasons(F4,172> 3.27,p< 0.05) (Table 2). Volumetric water content (θv) followed an opposite trend toTs(soil temperature), being lower in summer (7.3% ± 1%) compared to spring (14.6% ± 1.6%), winter (17.1% ± 1%), and autumn(17.7% ± 1%) (Table 3). For the period of the experiment,θvwas strongly af fected by the interacting ef fects of stocking × herbicide (F2,29= 8.06,p< 0.01) (Table 1). Signif icant interactions of stocking × fertilization (F2,29= 5,p< 0.05)and herbicide × clone (F4,172= 2.54,p< 0.05) were observed in autumn and spring, respectively (Table 2). No signif icant (p> 0.05) ef fects of silvicultural treatments onθvwere observed in summer (Table 2).

The combinedTsandθv-based model [Eq. ( 4)] was selected as best to predictFsas it yielded highestR2valuesand lowest RMSE compared toTs-based models across all levels of treatments (Table 4). TheQ10values from the combined model ranged from 2.91 to 5.23 and were marginally higher than the ones estimated from theTs-based model,with the highestQ10observed with clone 3 and the lowest in clone 2. Comparing across silvicultural treatments,Q10values were higher with clone 3, a stocking level of 1250 stems ha−1, and in unfertilized plots without weed control than in other treatments (Table 4). The slope betweenTsandFsincreased exponentially and was higher in fertilized plots(Fig. S1-A), and in plots without weed control (Fig. S1-B)than in unfertilized plots and in plots with weed control.The slope of the relationship betweenTsandFstended to be higher for the 1250 stems ha−1stocking than for stocking levels of 625 and 2500 stems ha−1(Fig. S1-C). For the model with clones, the slope ofTswithFswas signif icantly higher in clone 3 than in the other four clones (Fig. S1-D).The slope of theFs-Tswas positive but that of theFs-θvwas negative across all levels of treatments (Table 4). There was a strongly negative correlation between theTsandθv(r= − 0.89) (Fig. S2), indicating that soil temperatures were high when soil volumetric water was low, and vice versa. Therefore, in the regression models for the relationship betweenFsagainstTs, andθv, the estimated values of parameters a and b were always positive, and values of c always negative (Table 4).

Table 1 ANOVA statistics for the f ixed components of the linear mixed ef fect model for soil surface CO 2 ef flux( F s ), soil temperature ( T s ), and soil volumetric water content( θ v ) f itted for the period of the experiment. Fixed ef fects included stocking, clone,fertilization, and follow-up herbicide, and their twoway interactions and season.Degrees of freedom (df) for treatments and error used in the calculation of the F-statistic are presented

Table 2 ANOVA statistics for the f ixed components of linear mixed ef fect model for soil surface CO 2 ef flux ( F s ),soil temperature ( T s ), and soil volumetric water content ( θ v )f itted with the data separately for each season. Fixed ef fects included stocking (S), clone (C),fertilization (F), and follow-up herbicide (H) treatment, and their two-way interaction.Degrees of freedom (df) for treatments and error used in the calculation of the F-statistic are presented. Only signif icant results ( p < 0.05) are reported

Inf luence of season and silvicultural treatments on surface CO 2 ef flux

Values ofFswere strongly controlled by the ef fects of season(F3,889= 319.68,p< 0.001), stocking (F2,6= 9.92,p< 0.05),and clone (F4,889= 4.32,p< 0.01) (Table 1). No signif icant ef fects of fertilization or follow-up weed control, or twoway interaction between stocking levels, clone, fertilization,and weed control treatments onFswere observed (p> 0.05)(Table 1). AnnualFsestimated from the study site was on average 22.7 ± 7.1 t ha−1a−1for CO2(range 15.6–27.8). The rate ofFswas highest in autumn (27.7 ± 7.1 t ha−1a−1for CO2, range 25.2–32.5) and lowest in winter (15.6 ± 7.0 t ha−1a−1for CO2, range 14.4–17.4) (Table 3).

When seasonal data were examined separately, the clone signif icantly af fectedFsfor summer (F4,172= 2.68,p< 0.05),and autumn (F4,172= 7.74,p< 0.001) (Table 2). There were no signif icant dif ferences between mean soil ef flux rates for any clones during winter and spring. Clone 3 exhibited a consistently higherFscompared to other clones (Table 3).For all clones, values ofFswere at their highest in autumn and lowest in winter, while spring and summer showed intermediate rates between these two extremes (Fig. 2 a). Stocking levels signif icantly inf luencedFsin spring (F2,6= 17.69,p< 0.01) and summer (F2,6= 7.75,p< 0.05) (Table 2). In spring,Fswas highest (29.5 t ha−1a−1for CO2) for the 1250 stems ha−1stocking level and lowest (20.9 t ha−1a−1for CO2) for the 2500 stems ha−1stocking level (Fig. 2 b,Table 3).Fsvalues were consistently higher at a stocking level of 1250 stems ha−1compared to 625 (by 22%) and 2500(by 18%) stems ha−1over all seasons (Table 3). There were no signif icant main or interactive ef fects of fertilization and herbicide treatments onFs(p> 0.05) (Table 2).

Discussion

The first hypothesis thatFswould increase with stocking because of greater root and microbial biomass andcompetition, was only partially supported by the results of this study.Fsvalues were higher at a medium (1250 stems ha−1) stocking level compared to low (625 stems ha−1) and high (2500 stems ha−1) stocking level across all silvicultural treatments. Observed values ofFs(20.6–26.3 t ha−1a−1for CO2) were within the range reported by Noh et al.( 2010) for a Korean red pine (Pinus densifoliaSiebold &Zucc.) forest in Korea (22.8–27.3 t ha−1a−1for CO2) with the highest value at a medium stocking level, similar to this study. Other studies, however, have found that surface CO2ef flux increased with stand density (Litton et al. 2003b,2004) which might be explained by greater root and microbial biomass and higher litter production and decomposition(Litton et al. 2001) at higher densities. There are several possible causes whyFswas greatest at a medium (1250 stems ha−1) level of stocking. First, surface CO2ef flux may increase from a low to medium stocking level brought about by increases in root and microbial biomass. In addition,Fsmay decrease from a medium to a high level of stocking associated with (1) lower soil temperatures and less available water at high stocking levels or, (2) light becoming the most limiting growth factor triggering greater carbon allocation aboveground at the expense of belowground processes. The former may be more likely as our results showed that soil volumetric water content was signif icantly lower at 2500 stems ha−1by 2.6 and 1.6% compared to 625 and 1250 stems ha−1, respectively (Table 3).

Table 3 Soil surface CO 2 effl ux rates (mean ± SE), soil temperature (mean ± SE), and soil volumetric water content (mean ± SE) values observed by stockings (stems ha −1 ), clones (1–5), fertilization (Yes, No), and follow-up herbicide (Yes, No) treatments in P. radiata plantations during four seasons. Treatment means withina season followed by the same letter do not diff er signifi -cantly at α = 0.05 level using Tukey’s HSD test

The second hypothesis was that faster growing clones would show higher surface CO2ef flux levels, which is fully supported by this study. Clone 3, the fastest growing, had the highestFsaverage values (3–10%) compared with the other clones. This indicates that clone 3, having overall greater carbon assimilation, also allocated a greater proportion of f ixed carbon belowground compared to the other clones(Bown et al. 2009).

The third hypothesis for this study was that fertilization would not inf luence surface CO2ef flux as it was carried out 12 years before the measurements. There were no signif icant ef fects of fertilization on surface CO2emissions in any season during the year which is consistent with research on radiata pine in Chile (Bown and Watt 2016),slash pine in Florida, USA (Shan et al. 2001), and loblolly pine in Virginia (Tyree et al. 2006) and North Carolina,USA (Maier and Kress 2000). Our study, however, contains only one-year data and the absence of inter-annual variability may prevent f indingFsresponses to fertilization (Tyree et al. 2006). However, the insignif icant ef fects of fertilization on surface CO2ef flux in this study may be because the last fertilization was applied three years after planting and its ef fects after nine years might have ceased.It may also be because the fertilization level was too small to trigger a growth response (Tyree et al. 2006). At the same time, our temperate study site experiences strongwater limitations, particularly during summer, and therefore water rather than nutrients might be the major limiting factor af fecting plant growth (Davidson et al. 1998;Lavigne et al. 2004).

Table 4 Regression models for the relationship between F s , T s , and θ v across the clones (1–5), stocking levels (625, 1250, and 2500 stems ha −1 ), fertilization (Yes, No), and follow-up herbicide (Yes, No) treatments. Given a, b, and c are parameter estimates of the regression,RMSE is the root mean square error, R 2 is the coef ficient of determination, Q 10 is the temperature sensitivity index for F s (at 10 °C increase in T s )

Fig. 2 Seasonal dynamics of F s (μmol CO 2 m −2 s −1 ) across silvicultural treatments across f ive clones ( a), and three stockings ( b). Values are presented as least square mean (± 1 SE) of F s , by season. Treatment means within a season followed by the same letter do not dif fer signif icantly at α = 0.05 level using Tukey’s HSD test

The fourth hypothesis that there would be no ef fects of weed control on soil surface CO2ef flux was supported by this study. In contrast, research by Shan et al. ( 2001) in slash pine plantations in Florida, USA, indicated that the elimination of the understory signif icantly af fected surface CO2ef fluxes. This suggests that weed control reducedFsby decreasing below-ground biomass. However, we believe the insignif icant ef fects of weed control onFsin this study is the result of the time elapsed. Weed control was applied to all plots during the f irst two years, while total weed control was carried out prior to canopy closure in weed control plots only (Mason 2008). However, surface CO2ef flux measurements in this study were carried out at age 12, eight years after the follow up weed control when the ef fects of weeds were likely to have ceased.

The f ifth hypothesis that both soil temperature and soil water would control CO2ef fluxes across all silvicultural treatments is supported by this study. Collectively, both explain 27.9–48.9% of the ef flux variance as being signif icantly better to the model that considered only soil temperature (Table 4). Other studies have also reported that the combination of soil temperature and water can explain most of the variations in CO2ef flux as being the most important controlling factors (Gough and Seiler 2004; Liu et al. 2011). Soil temperatures contributed positively toFs, while soil water contributed negatively(Table 4). However, there was a strong, negative correlation between sol temperature and soil water (Fig. S2),indicating that soil temperatures were high when soil water was low and vice versa, which may confound the interpretation of the model. The temperature sensitivity of surface CO2ef flux (Q10) values in this study (2.9 to 5.2) across all silvicultural treatments were in the 1–10 range of other reports (Raich and Schlesinger 1992; Davidson et al. 1998;Gulledge and Schimel 2000; Xu and Qi 2001a, b) depending on the type of ecosystem and climatic conditions. TheQ10value in this study was highest for the fast-growing clone 3 at a stocking level of 1250 stems ha−1.

This study provides insight into how silvicultural management decisions may impact soil surface CO2ef fluxes and may contribute towards better estimates of carbon budgets in plantations. Surface CO2emissions varied with plantation density and clone, and with soil temperatures and water content, both contributing to the dif ferences in f luxes across seasons. Higher ef flux rates at a medium(1250 stems ha−1) stocking level compared to low (625 stems ha−1) and high (2500 stems ha−1) stocking levels were observed. There were no ef fects of fertilization and weed control after 12 years, indicating that the ef fects of these treatments might have ceased. Ef flux levels varied with clones, being higher in faster growing clones. In conclusion, surface CO2ef fluxes changed with silvicultural practices which might have implications for carbon accounting.

AcknowledgementsThanks to the New Zealand School of Forestry,University of Canterbury, for permission to access the experimental site and for arranging the necessary equipment during the research. The corresponding author thanks the NZ Ministry of Foreign Af fair and Trade (MFAT), as this research was partially supported by MFAT’s“NZAID Programme” as a postgraduate research allowance to the primary author, which facilitated the seasonal data collection. We would like to thank undergraduate as well as postgraduate students at the School of Forestry who contributed to f ield measurements. We are grateful to anonymous reviewers and editors for their insightful comments on the manuscript.

Author contributionsMohan KC, Euan G. Mason and Horacio E.Bown developed the concept for this manuscript. Mohan KC carried out f ield measurements, conducted data analysis, and drafted the manuscript under the supervision of Euan G. Mason and Horacio E. Bown.All authors contributed to subsequent writing, reviewed, and approved the f inal version of the manuscript.

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