Introduction

The carbon (C) sequestration in forest ecosystems has been an increasing concern for the world as a result of global climate change. Since the forest ecosystems have the most substantial quantities of carbon storage in terms of biomass and soil among the terrestrial ecosystems (Haripriya 2002), they emit a considerable amount of carbon to the atmosphere through respiration, photosynthesis, decomposition, and combustion (Hu and Wang 2008). The forest ecosystems with biomass, soil, litter, and coarse woody debris pools have a crucial role in the global carbon cycle as both carbon source and sink. The estimates made for Global Forest Resources Assessment 2010 (FAO 2015) presented that 53% (about 260 Gt C), 39% (about 189 Gt C), and 8% (37 Gt C) of stored carbon from the world forests and other wooded lands came from forest biomass, soil, and deadwood, and litterfall, respectively.

The spatiotemporal patterns of C storage in forest ecosystem pools are essential in understanding the consequences of land-use change on the global carbon cycle as it is the second major factor in controlling climate change (Houghton and Hackler 2000; IPCC 2007). Therefore, land use and land cover change (LULCC) is essential in examining the flows among different pools and carbon stock change. The main reasons of LULCC are natural or human-induced events such as deforestation, reforestation, and afforestation. The forests in Turkey have a long history of forest management interventions such as thinning and clear-cutting, agricultural expansion, and abandonment, forest rehabilitation, and deforestation that cause the conversion of land use. While population growth, depopulation of rural areas, agricultural land abandonment, expansion of forest areas, social-economic factors, and social pressure are regarded as the primary mechanisms for human-induced LULCCs, insect and fire damages are considered to be the primary mechanisms for natural-induced LULCCs (Pacala et al. 2001; Cayuela et al. 2006; Çakır et al. 2008).

As one of the signatory parties of the Kyoto Protocol, Turkey, is responsible for accurately monitoring, estimating, and reporting carbon stock changes concerning Articles 3.3 and 3.4 under forest management (UNFCCC 2008), some previous studies assessed such C stock levels in forest ecosystems based on remote sensing techniques in combination with field measurements. Patenaude et al. (2004) presented a canopy height quantile-based approach for quantifying aboveground carbon in the deciduous forest using lidar. García et al. (2010) used lidar height and intensity data to estimate aboveground biomass carbon stocks in mixed forests of central Spain. This research has demonstrated that intensity-based models obtained more accurate predictions of biomass. In a similar study, Ren et al. (2013) examined spatial and temporal patterns of tree biomass and soil carbon storage in forests of Guangdong, China, by using Landsat TM images and forest inventory data. Ren et al. (2014) analyzed spatial and temporal patterns of carbon storage in forest ecosystems, including tree biomass, understory, litter, and soil on Hainan Island, China, by combining field measurements with Landsat TM images. Thomas et al. (2008) indicated that the combination of lidar data and a height-structured ecosystem model could be a powerful tool to predict aboveground carbon dynamics even in mountainous terrain. Gunlu and Ercanlı (2018), on the other hand, made estimations on the aboveground carbon of pure beech forests in Turkey with ground measurements and Alos-Palsar image. Zhao et al. (2018) assessed a practical use of combined the repeat lidar data with field sampling data for monitoring temporal and spatial distribution of forest and carbon dynamics. In this study, the authors displayed the utility and potential of lidar data for monitoring forest resources. They highlighted, in particular, the realistic estimation ability of lidar depends on field surveys and high sampling rates. Since this method is quite costly and challenging, measuring the difference between C stocks at two distinct dates by predicting temporal changes in C density and land use is widely preferred instead. For this method, the forest inventory data and empirical approaches or allometric equations are regarded highly practical and reliable methods for estimating the forest biomass and carbon stock at a national or regional scale (Hu and Wang 2008). Though numerous studies on forest carbon sequestration obtained reliable results by using the forest inventory data and allometric equations, some limitations on C storage estimations lead to increasing uncertainties in forest C storage. For example, while neglecting C storages in understories, litterfall, and soil cause underestimation of carbon storages in forest ecosystems, using some fixed coefficient for coniferous and deciduous such as C coefficient, especially in mixed forests, results in inaccurate estimation (Chen et al. 2019).

Determining LULCC is a significant challenge in the management of forest resources because understanding historical dynamics in forest ecosystem structure and function has a crucial role in sustainable planning (Cannell et al. 1992; Dixon et al. 1994). However, the changes in forest structure in related to tree species, canopy cover, development stages, and stand ages, as well as LULCC, also affect carbon storages in the forest biomass (Zhou et al. 2008; Ren et al. 2011). Over the last few decades, there has been a considerable amount of research on land-use changes and their effects on forest ecosystems and soil degradation (Eaton et al. 2008; Cerdà et al. 2010). In recent years, numerous studies have concentrated on estimating the carbon sequestration in forest ecosystems, especially on the forest biomass (Başkent and Mumcu Küçüker 2010; Anonymous 2014; Mumcu Kucuker and Baskent 2015; Dong et al. 2015, 2018; Yang et al. 2018). Several other studies conducted on national, regional, and global scales have presented precise information about the effects of spatiotemporal changes of land use and their impact on the biomass carbon in the forest ecosystems (Sivrikaya et al. 2007; Yang and Guan 2008; Hu and Wang 2008; Muñoz-Rojas et al. 2011; Sivrikaya et al. 2013; Guo et al. 2013; Yang et al. 2017). Because most of these studies did not include C storages in understory, litter, and soil, C storages were mostly underestimated. While some studies estimated the effects of LULCC on soil organic carbon (SOC) stocks and SOC sequestration (Wellock et al. 2011; Ruiz Sinoga et al. 2011; Novara et al. 2012; Ren et al. 2014; Muñoz-Rojas et al. 2015), there has been limited effort to accurately quantify the effects of various land-use changes on C pools (Zhou et al. 2008; Arevalo et al. 2009; Kaul et al. 2009; Chen et al. 2019).

The primary purpose of this study, therefore, was to analyze the effects of spatial and temporal changes in the landscape structure of the Yeniköy forest planning unit on carbon sequestration in the forest ecosystems between 1972 and 2016. The secondary aims of this study are (1) to estimate carbon stock changes at various carbon pools such as forest living biomass, deadwood, litterfall, and soil in four consecutive periods (1972–1993, 1994–2003, 2004–2013, 2016–2025); (2) to examine the effects of LULCC on carbon stocks in terms of land cover type, development stages, age class and canopy cover in the area; and (3) to assess the spatial distribution of carbon density rate and carbon balance in the forest ecosystems between 1972 and 2016.

Material and methods

Case study area

The Yeniköy planning unit, located in Western Turkey, is approximately 11,150.3 ha in size, 91% of which is forested. The area extends along with UTM European 50 Datum 35, zone 604,000–628,000°E and 4,473,000–4,466,000°N. Its elevation varies between 0 and 835 masl. The forested areas are characterized by mid-slope terrain with an average slope of 33%. Beech (Fagus orientalis), oak (Quercus robur), alder (Alnus glutinosa subsp. glutinosa), ash (Fraxinus ornus), linden (Tilia tomentosa), and chestnut (Castanea sativa) trees are the dominant trees in the area. The mean temperature is 15.2 °C, and annual rainfall is 580.3 mm year−1 based on long term data series of the Karacabey meteorological station (DMI 2019) (Fig. 1).

Fig. 1
figure 1

The location of the Yeniköy planning unit

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Maps and inventory

In this study, both topographic maps and forest cover type maps at the 1/25000 scale for 1972, 1994, 2004, and 2016 were used. The forest cover type maps were derived by interpreting aerial photographs or high-resolution satellite images restored with the measurement of ground vegetation at 300- × 300-m intervals using systematic sample plots. Tree species and diameters at breast height (DBH) for all trees larger than 8 cm were measured, whereas tree height and age bark thicknesses, and radial growth for the last 10 years were measured only 3–5 trees in each sample plots. The timber volume of each tree was calculated by using the empirical yield table. The General Directorate of Forestry prepared all maps and field surveys based on forest management guidelines (Anonymous 2014). Forest area and timber volume in Turkey have been inventoried every 10 years since the 1960s using field surveys and remote sensing data. In some periods, however, the forest inventory could not be compiled due to some limitations like in 1983. Thus, the forest inventory database used in this study included only four inventory 10-year databases except that of 1983–1994.

The forest cover type maps in 1972 and 1994 were digitized, and the spatial databases were developed with maximum root-mean-square error under 5 m using Arc/Info GIS, and the forest cover type maps in 2004 and 2016 were supplied in digitized format. The growing stock of each forest type was obtained from Yeniköy forest management plans prepared in 1972, 1994, 2004, and 2016 (Anonymous 1972, 1994, 2004, 2016).

Biomass and carbon stocks

The forest carbon stock in this study was obtained by determining the total amount of carbon stored in above and belowground biomass (living biomass), deadwood, litterfall, and soil carbon pools separately. To specify the carbon stock change between different periods, the stock-difference method, which estimates the difference in total biomass carbon stock at time t2 and time t1, was used. The main reason for the selection of this method is that in Turkey the national inventory system for forests depends on measurement at periodic intervals. According to the Agriculture, Forestry and Other Land Use (AFOLU) guidelines, the annual carbon stock change between two periods and the carbon stock in the living biomass were calculated using Eqs. (1) and (2), respectively (IPCC 2006).

$$ \Delta C=\left({C}_{t2}-{C}_{t1}\right)/\left({t}_2-{t}_1\right) $$
(1)
$$ {C}_{\mathrm{LB}}=\left(\mathrm{GS}\times {\mathrm{BCEF}}_{\mathrm{I}}\right)\times \left(1+R\right)\times \mathrm{CF} $$
(2)

where ΔC is the annual change in forest carbon stock (t/ha/year), Ct1 and Ct2 are the carbon stocks in t1 and t2 years, respectively. CLB is the carbon stock in the living biomass (t), GS is the growing stock volume (m3), BCEFı is the factor for conversion and expansion of stem volume to aboveground biomass (AGB) (t/m3), R is the root to shoot ratio, and CF is the carbon fraction of dry matter. BCEFı is determined by multiplying of wood density (WD) and biomass expansion factor (BEF) coefficients (IPCC 2006).

In this study, species–species WD and BEF coefficients reported for each tree species in Turkey’s forests (Tolunay 2013) were used (Table 1). However, in case the country-specific coefficients were not developed for some tree species, as suggested by AFOLU, the coefficients given in the guidelines were used. The R and CF ratios given for temperate zone forests in AFOLU were used in the calculation (IPCC 2006) (Table 2).

Table 1 Wood density (WD), BEF, and BCEF values of the main tree species in Turkey (Tolunay 2013)
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Table 2 R and CF for different vegetation types given for the temperate zone forests in the AFOLU guide (IPCC 2006)
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Deadwood, litter, and soil carbon pools were estimated according to the country-specific coefficients for softwood and hardwoods in degraded and productive areas developed by Tolunay and Çömez (2008) (Table 3). The carbon stock in deadwood carbon pool was predicted by multiplying aboveground biomass, the ratio of deadwood biomass to aboveground biomass (1%), and carbon fraction (0.47) in Eq. [3]. The carbon stocks in litterfall (Eq. (4)) and soil organic matter (Eq. (5)) were estimated by multiplying the size of forest area and country-specific litter and soil organic carbon content (t/ha) for coniferous and deciduous species in productive and degraded areas (Table 3) (Tolunay and Çömez 2008).

Table 3 Country-specific litterfall and soil organic carbon content (t/ha) based on different vegetation types in productive and degraded areas (Tolunay and Çömez 2008)
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$$ \mathrm{DWC}=\mathrm{AGB}\times \mathrm{s}\times \mathrm{CF} $$
(3)
$$ \mathrm{LC}=F\times r $$
(4)
$$ \mathrm{SOC}=F\times r $$
(5)

where DWC is carbon stock in deadwood carbon pool (t), AGB is aboveground biomass (ton), s is the ratio of deadwood biomass to aboveground biomass, CF is carbon fraction of dry matter (tC), LC is litter carbon pool (t), SOC is soil organic carbon pool, F is the size of forest area (ha), and r is carbon content (tC).

Spatial distribution maps of carbon dynamics

To produce spatial distribution maps of C dynamics, forest cover type maps of Yeniköy planning unit for 1972, 1994, 2008, and 2016 were used. After creating a spatial database on digitized forest cover type maps, the volume of each cover type was joined to the spatial database using ArcMap10™, and C dynamics for each C pool were estimated using some function of GIS. The spatial distribution maps of total C dynamics were created by overlaying the spatial distribution maps of C dynamics in aboveground biomass, belowground biomass, deadwood, litter, and SOC pools for each inventory period separately. Besides, to map spatial change of C density, digitized forest cover type maps for 1972 and 2016 were intersected using GIS.

Results

Temporal change of carbon storage

Total C storage increased from 1135.2 Gg C in 1972 to 1816.6 Gg C in 2016 with a net accumulation of 681.4 Gg C. Over the four planning periods, net C gain was about by 24.8%, 12.3%, 14.1%, and 60.0% in between 1972–1993, 1994–2003, 2004–2013, and 1972–2016, respectively.

Total C density changed from 130.9 Mg ha−1 in 1972 to 153.5 Mg ha−1, 176.6 Mg ha−1, and 200.1 Mg ha−1 in 1994, 2004, and 2016, respectively. The annual forest C accumulation rates were 12.8 Gg year−1, 17.5 Gg year−1, 18.7 Gg year−1, and 15.5 Gg year−1 during 1972–1993, 1994–2003, 2004–2016, and 1972–2016, respectively (Table 4). Moreover, the annual forest C sequestration rates were 1.03 Mg ha−1 year−1, 2.31 Mg ha−1 year−1, 1.96 Mg ha−1 year−1, and 1.57 Mg ha−1 year−1 during 1972–1993, 1994–2003, 2004–2013, and 1972–2016, respectively.

Table 4 Temporal changes of C dynamics in different land cover types
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Change in carbon pools from 1972 to 2016

Total C storage and C densities of four forest C pools, including living biomass (aboveground and belowground biomass), deadwood, litterfall, and SOC, were calculated to compare the contributions of various C pools to total C storage (Fig. 2). While the most substantial amount of contribution to the C pool was from SOC, accounting for approximately 58.6% and 49.3% of the total C storage in the forest ecosystem in 1972 and 1994, respectively, living biomass was the most significant contributor in 2004 and 2016 by 54.0% and 57.7%, respectively (Fig. 2). The C pools in living biomass, deadwood, and litterfall accounted for approximately 38.5%, 0.3%, and 2.6% of total C storage in the forest ecosystem in 1972, respectively. Nearly 0.5%, 1.8%, and 40.1% of the total C storage were stored in the deadwood, litterfall, and SOC, respectively, in 2016.

Fig. 2
figure 2

Temporal change of forest C storage (a) and C density (b) in different C pools (SOC soil organic carbon)

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C densities in each pool increased gradually from 1972 to 2016 except for a slight decrease in SOC from 1972 to 1994. The total C density in living biomass ranged from 50.4 Mg ha−1 in 1972 to 115.4 Mg ha−1 in 2016. These values were 0.4–0.9 Mg ha−1, 3.4–3.6 Mg ha−1, and 76.7–80.2 Mg ha−1 in deadwood, litterfall, and SOC, respectively.

Total carbon storage in different land use/cover classes

Temporal change of total C and C density revealed an increasing trend in the different land cover types except degraded (D) and coppice (Cp) forests over four decades. While there was a particular increase in degraded areas from 535.7 ha in 1972 to 636.2 ha in 2016, total C was almost stable (Table 4).

The total C storage in different forest cover types varied, ranging from 0.2 Gg in 1972 to 620.7 Gg in 2016. Among five forest types, mixed (M) cover type was the largest contributor to biomass, soil, and total C storages in almost all periods. The contribution of mixed forests was nearly 55.7%, 54.0%, and 54.7% in 1972, 61.3%, 47.2%, and 61.1% in 2016, respectively, of total accumulation. Only in 1994 did hardwood forest type contribute the most to biomass, soil, and total C storages by 54.8%, 47.6%, and 51.1%, respectively (Fig. 3). The average C storages in softwood, hardwood, and mixed forest types were 7.1 Gg, 647.6 Gg, and 806.0 Gg, which accounted for 0.5%, 43.5%, and 54.1% of total C storage in the study area, respectively. The proportion of total C in hardwood and mixed forest types changed from 42.0% and 54.7% in 1972 to 37.1% and 61.1% in 2016, respectively (Table 4). This result indicated that hardwood and mixed forest types had played an important role as a C sink, unlike softwood forest types.

Fig. 3
figure 3

Temporal change of total C (a), biomass C (b), soil C (c) stocks, and forested areas (d) in different forest cover types. (S pure-softwood, H pure-hardwood, M mixed, D degraded forest; biomass C includes living and deadwood C; soil C includes litter and SOC)

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The proportion of biomass C in hardwood and mixed forest types changed from 41.2% and 55.7% in 1972 to 38.2% and 61.3% in 2016, respectively (Fig. 3). The proportion of soil C in hardwood and mixed forest types changed from 42.4% and 54.0% in 1972 to 35.6% and 60.9% in 2016, respectively. During the 44 years, hardwood and mixed forests sequestrated about 198.3 Gg C and 489.9 Gg C with an average C accumulation rate of 4.5 and 11.1 Gg year−1.

The C density in different forest cover types had an extensive range from 25.8 to 220.2 Mg ha−1. The lowest C densities occurred in degraded and coppice land cover types in each period, with the average C density of 28.29 Mg ha−1. However, the highest C densities occurred in hardwood forest type in almost all periods, with the average value of 187.90 Mg ha−1 and followed by mixed forest type, which accounted for about 179.83 Mg ha−1 of average C density (Table 4).

The change in the forest C stocks for land use classes in the study area can be explained by increasing the quality of forest ecosystem structure for about four decades. Transitions of land use classes from 1972 to 2016 indicated that the degraded areas turned into productive softwood (S) or hardwood forests by about 56.2%, coppice forest was converted to high and productive forests by 81%, respectively. Besides, bare forest lands changed to hardwood or mixed hardwood forest by 18% and degraded areas by 15%, and non-forest areas were converted to forest areas by about 18.8% from 1972 to 2016 (Table 5).

Table 5 Transitions between land cover types from 1972 to 2016
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Total carbon storage in different development stages

While the proportion of C in regenerated (a) and young (b) stands decreased from 2.2% and 91.5% in 1972 to 1.3% and 5.3% in 2016, the proportion of C in mature (c) and over-mature (d) increased from 0.0% and 2.9% in 1972 to 86.2% and 6.3% in 2016, respectively. A large number of contributions were observed in young development stages, with 91.5% and 57.0% in 1972 and 1994, respectively, and mature development stages with 86.9% and 86.2% in 2004 and 2016 due to increasing areas. C densities in different development stages have slightly increased from 1972 to 2016 except the regenerated areas. While the largest C density was made up by over-mature areas (157.9 Mg ha−1) in 1972, it was provided by mature areas (193.2, 206.7, and 224.0 Mg ha−1) in the following periods. Average C densities in different development stages varied largely, ranging from 91.64 to 207.95 Mg ha−1. Mature development stages had the highest average C density (208.0 Mg ha−1) with the minimum and maximum of 193.2 Mg ha−1 and 224.0 Mg ha−1, respectively. The average C densities in over-mature and young development stages were in the middle of the range. The lowest average C density was obtained in the regenerated areas with a value of 91.64 Mg ha−1 (Table 6).

Table 6 Temporal changes of C dynamics in different development ages
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While in 1972 the area was mostly clumped into young development stages, in 2016, the areas were concentrated into mature and over-mature stages. Table 7 demonstrates that the regenerated lands in 1972 turned into young and mature development stages by 71%, young areas changed to mature and over-mature stages by 90%, degraded changes to young and mature stages by 56.2%, coppice forests converted to young and mature stages by 79%, bare forest lands converted to mature stages by 16%, and non-forest areas converted to young, mature, and over-mature by 11.2% in 2016. These positive transformations, as well as increasing forest areas through afforestation, led to the accumulation of carbon stock in the forest ecosystems.

Table 7 Transitions between development stages from 1972 to 2016
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Total carbon storage in different canopy cover types

The effects of the changes in forest structure on C dynamics were analyzed in terms of canopy cover classes. As expected, the lowest level of C storage obtained for low coverage areas in 1972 (11.9 Gg C) and 1994 (20.8 Gg C) and regenerated areas 2004 (12.3 Gg C) and 2016 (14.8 Gg C). The highest level of C storage in all periods occurred in full coverage areas by 85.4%, 91.8%, 86.0%, and 85.7% in 1972, 1994, 2004, and 2016, respectively, due to large amounts of forest biomass and areas. The annual C accumulation rate was 15.5 Gg year−1 with a range from − 0.5 Gg year−1 in coppice areas to 13.2 Gg year−1 in full coverage areas. Consequently, full coverage type has contributed most of C sequestration with net accumulation 581.7 Gg C and an average C accumulation rate of 13.2 Gg year−1 during 1972–2016 (Table 8), which accounted for 85.4% of total forest C accumulation over 44 years. C densities in canopy closure of low, medium, and full coverage areas have increased from 1972 to 2016 based on growth rate.

Table 8 Temporal changes of C dynamics in different canopy cover
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During the period from 1972 to 2016, the increasing general forest areas and the quality of forest structure with decreasing degraded areas and bare forest lands due to afforestation and reforestation and the increasing growth rate of existing forests were the most critical factors of the C dynamics. The generated areas that were transformed to medium and full covered lands in terms of crown coverage areas were nearly 60%; low and medium covered areas transformed to full covered areas were 71% and 55%, respectively; and the degraded and coppice forests that were converted to medium and full covered areas were 41% and 76% from 1972 to 2016 (Table 9). These transformations from 1972 to 2016 contributed to a considerable rise in total C. While the maximum C densities occurred in full coverage areas, the minimum C densities occurred in degraded lands due to low forest biomass.

Table 9 Transitions between canopy cover from 1972 to 2016
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Total carbon storage in different age classes

The study area was classified into five age classes: young (0–20 ages), middle-aged (21–40 ages), immature (41–60 ages), mature (61–80 ages), and over-mature (81–120 ages) forests. The highest total C storage occurred in mature forests with 471.4, 1303.9, and 770.9 Gg C in 1972, 2004, and 2016, respectively, and in immature forests with 1142.5 Gg C in 1994. The proportion of these age classes in the general forest areas was higher than those of other age classes. The lowest total C occurred in young forests with 24.6, 50.2, and 23.1 Gg C in all periods 1972, 1994, and 2016, respectively, except 2004. Total C storage was mainly stored in middle-aged and immature forests accounting for 47.5% and 94.0% of total forest C storage in 1972 and 1994, respectively. However, it was mainly stored in mature and over-mature forests, accounting for 81.9% and 88.7% of total forest C storage in 2004 and 2016, respectively. This result was due to the distribution of the study area to different age classes. While the C density decreased by 7.4% in young forests, C densities increased in the other age classes (middle-aged, immature, mature, and over-mature) by 3.3%, 13.1%, 47.7%, and 43.6%, respectively, from 1972 to 2016. The maximum C accumulation from 1972 to 2016 was provided by over-mature forests (81–120 age class) with 777.8 Gg C at an average rate of 17.7 Gg year−1. However, the maximum annual C accumulation rate was obtained by mature forests with 1.63 Mg ha−1 year−1 (Table 10).

Table 10 Temporal changes of C dynamics in different age classes
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Spatial distribution of total carbon

The spatial distributions of total forest C density and forest biomass C density in 1972 and 2016 in the Yeniköy planning unit are depicted in Figs. 4 and 5. The dark green colors indicate high C density, while the light green colors indicate low C density. The spatial distribution of forest and biomass C densities in 1972 and 2016 were not homogenous across the Yeniköy planning unit. There was a considerable spatial difference in C densities between 1972 and 2016. About 23.2% and 21.0% of the total area in 1972 and 2016, respectively, did not contribute C stock due to lack of biomass. According to the maps depicting total C density (Fig. 4) and biomass C density (Fig. 5), the dark green areas were more in 2016 than in 1972, indicating a relative increase in forest C density. Approximately 56.1% of the total area had 201–300 Mg ha−1 total C density in 2016, while there was not an area with this C density in 1972. In 2016, only 16.8% of the total area had 100–200 Mg ha−1 total C density, while in 1972, 61.3% of the total area was at this density. While forest biomass C density ranged from 0 to 94 Mg ha−1 in 1972, it ranged from 0 to 210 Mg ha−1 in 2016. Forest biomass C density mostly clumped into 101–250 Mg ha−1 in 2016 by about 57.4%; however, it accumulated into 51–100 Mg ha−1 in 1972 by about 54.5%. The total and biomass C densities were higher in the south and west than in the east and north for each corresponding period.

Fig. 4
figure 4

Spatial distribution of total C density in 1972 (a) and 2016 (b)

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Fig. 5
figure 5

Spatial distribution of biomass C density in 1972 (a) and 2016 (b)

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The spatial distributions of C balance for total forest C and forest biomass between 1972 and 2016 in the Yeniköy planning unit are shown in Fig. 6. The terms “increased,” “decreased,” and “unchanged” mean increasing, decreasing, and unchanging forest carbon stocks for total or only biomass, respectively, from 1972 to 2016. During the period from 1972 to 2016, the C stock increased in the majority (74.0%) of the study unit, while it decreased in a small part (10.0%) of the area.

Fig. 6
figure 6

Spatial distribution of forest C balance from 1972 to 2016

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Discussion

The total C storage in the forest ecosystem in Yeniköy planning unit ranged from 1135.2 Gg C in 1972 to 1816.6 Gg C in 2016 in which the C densities increased from 130.9 to 200.1 Mg ha−1. The estimated increase in C storage was attributed to the increase in the forest coverage area and the C density of existing forests with the biomass growth in the study area for the period between 1972 and 2016. Despite the fixed boundary of the study area, the forested area has increased at a rate of 4.68% from 1972 to 2016. The annual forest C sequestration rates of 1.57 Mg ha−1 year−1 between 1972 and 2016 as estimated in this study was significantly higher than earlier estimates made for different study areas in Turkey by Sivrikaya et al. (2007) (0.67–0.04 Mg ha−1 year−1), Sivrikaya et al. (2013) (0.11 Mg ha−1 year−1), Tolunay (2011) (0.21 Mg ha−1 year−1), and Kucuker (2020) (1.18 Mg ha−1 year−1). The differences in forest C sequestration rates among these studies may be due to several reasons. First, the methods used to calculate C storage were different. In this study, a more detailed method of calculation for C was used. For example, the species–species coefficients of WD and BEF were preferred rather than the general ratios for hardwoods and softwoods. Second, these reports on forest biomass C storage, except for Kucuker (2020), did not include deadwood, litterfall, and SOC stocks. Although many studies about the temporal change of C stocks focused on C storage in only living biomass, this paper focused on the C storages in deadwood, litterfall, and SOC in addition to living biomass. Total C storage of four forest C pools, including living biomass, deadwood, litterfall, and SOC, increased from 1972 to 2016.

While the most considerable contribution to total C storage was by SOC in 1972 and 1994, which accounted for 58.6% and 49.3%, it was from living biomass (above and belowground biomass) in 2004 and 2016, which accounted for 54.0% and 57.7%. Moreover, the total contribution of C storage in deadwood, litterfall, and SOC was about 61.5% and 42.3% in 1972 and 2016, respectively. The results of the study demonstrated that leaving the other carbon pools (deadwood, litterfall, and SOC) out caused the underestimation of C storage and C density. Ren et al. (2014) found out that of the total C storage, about 75.1% and 22.3% were stored by the soil and tree layers, respectively, in Hainan Island in China. Cui et al. (2015) indicated that the forest soil was the largest C pool, which accounted for more than 70% of the total C storage in Shaanxi province in China. Besides, tree and soil layers stocked almost all C storage of forest ecosystems accounting for 97.5% in this area. Chen et al. (2019) figured out that the largest C pool for Hunan province, China, was stored in soil with about 78.0% of the total C storage and followed by tree layer with 17.3%. Also, this study indicated that the soil layer had the most substantial proportion of total C density in the forest ecosystem and the proportion of C density in tree layer followed to the soil in Hunan Province, China. Zhou et al. (2008) reported that the C pools in litterfall and understory vegetation accounted for 38–44% of total C storage. Thus, they should not be neglected in the estimation of total C storage.

Total C storage in the forest ecosystem increased by about 681.40 Gg from 1972 to 2016, including 615.16 Gg and 66.23 Gg of biomass C and soil C, respectively. While soil C density in the study area increased from 80.11 to 83.82 Mg ha−1, biomass C density increased from 50.78 to 116.26 Mg ha−1 over four decades. The result indicated that the C sequestration potential in forest biomass in the Yeniköy planning unit plays a more significant role than in forest soil. Therefore, the changes in forest structure supporting growing stock in terms of tree species, development stage, coverages, and age class distribution related to rotation ages are very effective components on C storage induced global climate change. Besides, in this study, SOC was estimated based on some allometric equations concerning various vegetation types for coniferous and deciduous in the literature. However, SOC is a function of several factors such as climate, topography, soil type, and biophysical factors of soil. Therefore, future detailed research should be focused on the calculation of SOC for accurate estimation of C sequestration in forest ecosystems.

Land use, forest cover types, tree species composition, and forest structure in terms of age, development stages, and canopy cover are essential driving factors influencing C dynamics (Kucuker 2020; Chen et al. 2005). Among the total 681.4 Gg C sequestration over four decades, softwood, hardwood, and mixed forest cover types sequestrated 14.5 Gg, 198.3 Gg, and 489.9 Gg, respectively. Mixed forests, composed mostly of hardwoods, acted as a C sink in the forest ecosystem, with 71.9% of total C sequestration. The large forest area and high standing timber volume of mixed forests were the main reason for the highest C stock. On the other hand, hardwoods acted either as a C sink with 198.3 Gg accounting for 29.1% of total C sequestration. Total C storage in the productive areas in the Yeniköy planning unit showed an increasing trend over four decades due to increasing productive forest areas and growth rates. However, total C storage in degraded areas slightly decreased despite the increase in degraded areas. Low growing stocks can explain that in degraded areas. This result was supported by some previous studies reported by Chen et al. (2019), He et al. (2013), Chen et al. (2005), and Kucuker (2020), who indicated that hardwood forest storage more C than softwood forests.

While the highest C density was found in hardwood forest types, the lowest C density was found in degraded forests. The temporal change in forest cover types based on some forest management interventions or some natural events resulted in the change in total C storage. The contribution of mixed forests, which was mostly by hardwoods to total C storage, was higher than hardwood forests. The C density in hardwood forests, however, was much higher than that of the other forest types. The increase in mixed forest areas by 23.6% and the decrease in hardwood forest areas by 8.0% over four decades caused this result. The conversion from low C density forests such as coppice and degraded to high and productive forests that have higher C density, especially in the mixed forests increased C storages. Under the national forestry policy, the General Directorate of Forestry in Turkey has begun to implement “the action plan to converse coppice into high and productive forests” since 2006. Over four decades a total area of 568.3 ha, 124.9 ha, and 334.8 ha was converted to hardwood and mixed forests, respectively. Consequently, the growing stock, biomass, and C storage in these areas increased compared to coppice or degraded areas (Sivrikaya et al. 2013). Moreover, the conversion from the bare forest and non-forest areas as well as low C density forests into productive woodland or higher C density forests increased forest coverage and total C storage. Over the last four decades, the conversion of some agricultural areas in the study area to forest coverage by natural ways or afforestation contributed to total C storage. Similarly, Chen et al. (2019) indicated that the conversion of about 140.9 × 104 ha of agricultural areas to woodland within the scope of a program launched in Hunan Province increased forest coverage and C storage. Some researchers demonstrated that an increase in forest cover due to abandoned agricultural areas, productive forest areas, and protected forest areas as well as decreasing non-forest lands and degraded forest lands increased forest C storage (Sivrikaya et al. 2007; Sivrikaya et al. 2013; Kucuker 2020). The state forest enterprise has made a great effort to increase the secondary incomes of forest villagers through non-wood forest products. For this purpose, some areas were afforested by stone pine to allow corn production as well as with poplar and scots pine. Besides, the evaluation of the planning approach from a timber-based planning approach to the ecosystem-based planning approach in Turkey has played an essential role in C sequestration. Also, this study area gained more attention with the production of linden flowers, chestnut fruits, and bay laurel. The state forest enterprise offered the tenancy of some degraded areas to forest villagers to provide bay laurel production (Kucuker and Sarı 2019). Linden tree, chestnut, and bay laurel lands were planned for non-wood forest products instead of timber production. The increase in the awareness of and sensitivity to the forest ecosystems in this area and the protection of plant resources resulted in protecting these crucial sources of income and increase C storage.

Over four decades, the increase in total C storage was attributed to the improvements in forest coverage and C density in existing forests due to growing stock. The mature development stage has played a significant role in C storage with the highest average C density (208.0 Mg ha−1). The main reason for the low C density in 1972 and 1994 was that 81.8% and 50.6% of the forested areas consisted of young development stages with lower C density. The proportion of the areas of mature development stages in the study area accounting for 77.0% and the higher C density in biomass resulted in a large amount of C storage, which accounted for 87.0% in 2016. The mature development stage has played an essential role in carbon sequestration with net accumulation 1566.0 Gg C and an annual C accumulation rate of 35.6 Gg year−1 during 1972–2016.

Similarly, fully covered forest types have contributed significantly to the C sequestration by accounting for a significant percentage (85.4%) due to growing stock. The cause of the lower C storage in the regenerated and degraded lands was mainly the small amount of forest biomass and forested areas. The results demonstrated that full coverage areas played a significant role in the carbon sequestration due to their higher growing stock. These results were supported by Kucuker (2020) and Tuyoglu (2020), who analyzed the temporal change of C dynamics in the Akçaabat and Oltu regions in Turkey, respectively.

In 1972 and 1994, 50.1% and 93.2% of the whole area were covered with middle-aged and immature forests, and in 2004 and 2016, 78.7% and 84.3% of the whole area were covered with mature and over-mature forests. The lowest C densities obtained from the regenerated forests for each period were due to low aboveground C biomass. The increase in wood biomass based on age and growing wood stock caused an increase in C densities from first age class to last age class for each period. Therefore, mature forests had a maximum annual C accumulation rate with 1.63 Mg ha−1 year−1. As reported in previous studies for various forest ecosystems, the total C storages and the C density of the forest ecosystem varied based on forest ages (Wang and Feng 2000). Zhou et al. (2008) indicated that most of the total C storage was stored in the middle-aged and immature forests. Yang and Guan (2008) found that potential C storage can reach a significant level if the young and middle-aged forests develop rapidly to mature forests giving their high C density. Similarly, Chen et al. (2019) demonstrated that the increase in C storage over time was related to the increase in forest area and the C density of available forest with higher ages.

The spatial C distribution maps in the forest planning unit and the changes over 44 years in the past were compiled by using GIS technology. The spatial distribution of C density in the study area was heterogenic (Figs. 4 and 5). The difference in the spatial distribution of C dynamics was highly related to the temporal change in the forest cover type, forest structure, and growing stocks (Fig. 7). The most important contributors were the increases in the forest area by 4.68%, the afforestation of bare forest land by 33.9%, the increases in the productive forest areas with the rehabilitation of degraded areas by 56.2%, the conversion of coppice to the high forest by 90.2%, and the forestation of abandoned agricultural lands by 18.8%. Besides, the transformation of the area with low C density into the mixed and hardwood forest cover types, which accounted for 1908.1 ha and 390.3 ha; to the mature and over-mature development stage, which accounted for 6788.5 ha and 563.0 ha; to the full coverage areas, which accounted for 1213.5 ha; and older age classes, which accounted for 2941.6 ha contributed to the increased areas in C balance change. Therefore, the change in land use, land cover type, species composition, and forest structure were crucial factors in spatial C dynamics. Besides, the human population movement, forest management interventions, afforestation and reforestation activities, forest policy, and socio-economic structure were the driving factors on the spatiotemporal change of C dynamics (Kucuker 2020; Tuyoglu 2020).

Fig. 7
figure 7

Spatial distribution of forest cover types in 1972 (a) and 2016 (b)

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Conclusion

The present study analyzed the temporal and spatial patterns of C dynamics on various C pools in the Yeniköy forest planning unit over four decades based on forest inventory data using the latest methodology of IPCC 2006 guidelines. The results demonstrated the importance of land use, land cover change, and the quality of forest ecosystem structure characterized by land cover type, developing stages, age class, and canopy cover on carbon dynamics and its spatial distribution.

The total C storage in the forest ecosystem in the Yeniköy planning unit increased by 681.4 Gg over four decades. The annual forest C sequestration rate was 1.57 Mg ha−1 year−1 between 1972 and 2016. The results indicated that the total contribution of C storage in the deadwood, litterfall, and SOC pools was about 61.5% and 42.3% in 1972 and 2016, respectively. This result clarified that neglecting these C pools would result in a significant error in the calculation of total C storage of forest ecosystems.

The results indicated that the land use and land cover changes significantly accounted for C dynamics and spatial distribution of carbon density. As known, the land cover composition and differences are significant factors in forest management in understanding the historical dynamics of C sequestration in forest ecosystems. The transition from degraded, coppice, bare forest, and non-forest areas to productive woodland resulted in an increase in forest coverage and total C storage. Although mixed forest type composed mostly of hardwoods was the most significant contributor to biomass, soil, and total C storages, the highest C densities occurred in the hardwood forest type. These results have significant implications on the species selection in afforestation or reforestation activities to maximize C sequestration in the forest ecosystems.

The quality of forest ecosystem structure in terms of development stages, crown closure, and age class distribution can have a serious effect on the C dynamics. Mature development stage, fully covered forest types, and over-mature forests have played a significant role in C sequestration with the highest average C density of 208.0, 189.27, and 194.03 Mg ha−1 over four decades. Therefore, improving forest structure concerning development stages, canopy closure, and age class distribution, as well as forest management actions such as harvesting, will be effective ways to ensure maximum C storages.

The spatial distribution of C density in the Yenikoy planning unit was heterogenic. The change in land use, land cover type, species composition, and forest structure were the main reasons for the spatial heterogeneity. The maps providing a visual presentation of C densities were vital instruments for forest managers for accurate and practical decision-making and for identifying where improvements can be made. The evaluation of the effects of spatial and temporal change in forest ecosystems on C dynamics, as well as an accurate and reliable estimation of C pools, are critical in determining effective and appropriate forest management practices for the ecological sustainability of C products and mitigating climate change effects.