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Tongetal. Annals of Forest Science (2024) 81:12
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Annals of
Forest Science
Canopy gap impacts onsoil organic carbon
andnutrient dynamic: ameta-analysis
Ran Tong1, Biyong Ji2, G. Geoff Wang3, Chenyang Lou1, Cong Ma1, Nianfu Zhu1, Wenwen Yuan1 and
Tonggui Wu1*
Abstract
Key message The forest canopy gaps, formed by natural or anthropogenic factors, have been found to reduce soil
carbon content and increase nutrient availability. The magnitudes of these effects have been observed to increase
with gap age and size, and are largely influenced by changes in temperature, precipitation, and solar radiation.
Context Local studies have illustrated the influence of canopy gaps on the spatial heterogeneity of soil carbon
and nutrients, playing a pivotal role in driving forest regeneration and succession. Nevertheless, it remains largely
unknown whether the response of soil carbon and nutrient content to gap formation is consistent across forest eco-
systems at global scale.
Aims The aim of this paper is to assess the homogeneity of the observed responses of soil carbon and nutrients fol-
lowing gap formation among a wide array of forest ecosystems and climatic regions.
Methods We performed a meta-analysis synthesizing 2127 pairwise observations from 52 published articles to quan-
tify the changes in in soil physical, chemical, and microbial variables resulting from gap creation in natural forests
and plantations spanning tropical to boreal regions.
Results Canopy gaps resulted in significant decrease of soil organic carbon (Corg) and microbial carbon (Cmic). The
concentrations of ammonium (NH4+), nitrate (NO3−), and available phosphorus (available P) increased following gap
creation. These changes mainly occurred in the growing season and in the mineral soil layer, becoming more pro-
nounced with increasing gap age and size. The change in Corg was negatively regulated by mean annual precipitation,
and was associated with the changes in Nt and Nmic. The change in NH4+ was positively regulated by mean annual
temperature, and was associated with the changes in available P and oxidoreductases (Ox-EEAs). The model explain-
ing the change in soil carbon content exhibited a higher explanatory power than the one accounting for changes
in soil nutrient availability.
Conclusion The results indicated that forest canopy gaps resulted in a reduction in soil carbon content
and an increase in nutrient availability. These findings contribute to a better understanding of the role of small-scale
disturbances as drivers of forest ecosystem succession.
Keywords Canopy gaps, Soil organic matter, Nutrient cycling, Topsoil properties, Climate effects, Forest ecosystems
Handling editor: Andreas Bolte.
This article is part of the topical collection on: Impacts of disturbances on
carbon cycling in forest ecosystems.
*Correspondence:
Tonggui Wu
wutonggui@caf.ac.cn
Full list of author information is available at the end of the article
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Tongetal. Annals of Forest Science (2024) 81:12
1 Introduction
Canopy gaps widely occur in forest communities and are
mainly formed by natural treefalls or as a consequence of
selective logging (Pollmann 2002). e heterogeneity of
environmental resources caused by the occurrence of can-
opy gaps drives plant community succession (Fahey and
Puettmann 2008; Kelemen etal. 2012; McNab etal. 2021).
Numerous studies have shown that canopy gap dynamics,
along with the resulting variations in light, temperature, and
soil moisture regimes (Gray etal. 2002; Ritter etal. 2005;
Galhidy etal. 2006), generally promote forest regeneration
and succession (Yamamoto 2000; Dechnik-Vazquez etal.
2016; Zhu etal. 2021; Lu etal. 2023). For instance, a global
meta-analysis demonstrated that canopy gaps enhanced
woody plant regeneration and that the effects were influ-
enced by gap characteristics, such as gap age and size, and
environmental factors (Zhu etal. 2014). Meanwhile, recent
local studies have reported that the plant community suc-
cession and microclimatic change following canopy gap
creation exert certain impacts on the soil carbon flow and
nutrient cycling (Gough etal. 2021; Griffiths etal. 2021).
Forest regrowth following disturbances plays a crucial role
in facilitating the terrestrial biosphere’s noticeable absorp-
tion of anthropogenic CO2 emissions (Pugh etal. 2019; Jay-
akrishnan etal. 2022). Nevertheless, the impacts of creating
canopy gaps on soil carbon fractions have shown ambiguity,
with reports of both positive and negative effects, as well as
instances where no impact was observed (dos Santos etal.
2016; Amolikondori etal. 2022). To a considerable extent,
this disparity can be accounted for by the reality that can-
opy gaps modify the decomposition patterns of soil organic
matter, thereby impacting the storage of carbon in the soil.
Simultaneously, canopy gaps elevate environmental hetero-
geneity, giving rise to distinct microbial community struc-
tures and vegetation compositions. is, in turn, influences
the input of exogenous organic carbon into the soil.
Mounting evidence suggests that soil nutrient availability
stands out as a primary limiting factor for forest primary
productivity, co-regulated by plant diversity and species
turnover throughout the stages of forest succession (Long
etal. 2018; Liu etal. 2021; Joshi and Garkoti 2023). Typically,
canopy gaps play a role in expediting soil nutrient cycling
within forest successional processes, encompassing nutrient
release, migration, and transformation (Muscolo etal. 2014).
In addition, canopy gap characteristics, including size, spa-
tial pattern, locations, and frequency, can influence light and
water distribution as well as rates of litterfall decomposition,
potentially leading to changes in nutrient availability (Zhang
and Zak 1995; Eysenrode etal. 2002; Prescott 2002; Mataji
and Vahedi 2021). Hence, it is imperative to investigate the
alterations in soil nutrient availability following gap crea-
tion, aiming to discern the potential ramifications on forest
regeneration and succession within forest ecosystems.
e heightened levels of light, temperature, and rain-
fall, coupled with diminished plant nutrient uptake, may
collectively govern soil carbon and nutrient dynam-
ics following gap formation. e impacts of canopy gap
creation on forest regeneration and succession are closely
associated with climate conditions at larger spatial scales
(Ackerly 2003; Zhu etal. 2014; Pope et al. 2023). Fur-
thermore, there is a well-established correlation between
the characteristics of canopy gaps and the composi-
tion as well as dynamics of forest stands (Kneeshaw and
Bergeron 1998; Ren etal. 2021). erefore, future climate
condition changes would greatly increase the uncertainty
of the impacts of canopy gap creation on soil carbon and
nutrient availability across various forest types.
e objectives of this paper are: (1) to investigate the
effects of canopy gaps on carbon content and available
nutrients; (2) to identify when and where canopy gaps
may significantly impact soil carbon content and available
nutrients; (3) to assess whether climate conditions would
promote or constrain the effects of canopy gaps on soil car-
bon sink and fertility. Our findings will not only broaden
the understanding of the response of the soil carbon pool
and nutrient availability to small-scale disturbances but
also aid in exploring the potential mechanisms of canopy
gap effects on forest regeneration and succession.
2 Materials andmethods
2.1 Data collection
We compiled our dataset by collecting articles published
before September 2021 from the Web of Science and China
National Knowledge Infrastructure (CNKI). e keyword
combinations used for retrieval were (("canopy gap" OR
"treefall gap" OR "forest gap") AND ("soil" OR "microbial"
OR "soil enzyme") AND ("carbon" OR "nitrogen" OR "phos-
phorus" OR "nutrient" OR "stoichiometry"). To avoid unin-
tentional biases, we developed the following criteria to
select pooled articles: (i) the article had to be a field survey
conducted in forest areas; (ii) both canopy gaps and forest
understory control treatments were reported; (iii) canopy
gaps underwent strict natural recovery processes without
artificial nutrient input or tree planting; (iv) if the study con-
tains samples from multiple time points, the data applied to
analyze the canopy gap effects for the growing season and
non-growing season was extracted from the middle of the
growth season and the end of non-growing season, respec-
tively; (v) information on the sample size and the means
of control and treatment groups were explicitly reported
(Fig. 10 in Appendix). In total, 2127 paired observations
were extracted from 52 articles that met the abovemen-
tioned criteria (Text 1 in Appendix), and the dataset was
made publicly available in the Figshare repository (Tong
etal. 2023). e geographic distribution of the canopy gap
experiments in the meta-analysis is shown in Fig.1.
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Tongetal. Annals of Forest Science (2024) 81:12
2.2 Data compilation
e variables extracted from the included studies were
classified into five main groups: (i) basic soil characteris-
tics (i.e., pH, soil moisture, and soil temperature), (ii) soil
organic carbon and total nutrients (i.e., soil organic carbon
[Corg], total nitrogen [Nt], total phosphorus [Pt], and ratio of
soil organic carbon to total nitrogen [C:N]), (iii) soil avail-
able nutrients (i.e., ammonium [NH4+], nitrate [NO3−],
and available phosphorus [available P]), (iv) the activities of
extracellular enzymes (i.e., hydrolases [Hy-EEAs] and oxi-
doreductases [Ox-EEAs]), and (v) soil microbial biomass
carbon and nutrients (i.e., microbial biomass carbon [Cmic],
microbial biomass nitrogen [Nmic], microbial biomass phos-
phorus [Pmic], and the ratio of microbial biomass carbon to
microbial biomass nitrogen [Cmic:Nmic]). For each observa-
tion, we also recorded the other parameters, such as the
latitude and longitude of the experimental locations, cli-
mate patterns encompassing the mean annual temperature
(MAT) and mean annual precipitation (MAP), forest type
(natural forest and plantation), and other information (can-
opy gap age and size, sampling time and location). We also
extracted each sampling site’s mean UV radiation data from
a global dataset (http:// www. ufz. de/ gluv) (Beckmann etal.
2014). e correlation between geographical and climatic
variables is shown in Table1 in Appendix. e mean (
X
),
sample size (n), and standard deviation (SD) of all variables
were extracted from the original articles. If the study used
standard error (SE) rather than SD, we used
SD =SE ×√n
to calculate SD. When some studies did not report the
SD or SE (n = 283), we multiplied the reported mean by
the average coefficient of variance of the complete dataset
to calculate the missing SD (Weir etal. 2018). Data were
directly obtained from the table or text, and those in digi-
tized graphs were extracted with Getdata Graph Digitizer
(version 2.22, Moscow, Russia).
We subdivided the potential categorical variables influ-
encing changes in soil carbon content and available nutri-
ents following gap creation. ese variables encompassed
sampling time (growing season and non-growing sea-
son), sampling location (gap center and gap edge), sam-
pling layer (mineral layer (0–30cm) and organic layer),
gap origins (natural and artificial), gap age (≤ 3, 4–10,
and > 10 years), and gap size (≤ 100, 101–400, and > 400
m2). We established these thresholds for potential cat-
egories primarily by referencing previous meta-analyses
(e.g., Zhu etal. (2014)), determining general breakpoints
from manipulative canopy gap experiments within our
dataset, and analyzing the data distribution of numerical
variables related to canopy gap characteristics (Fig.12 in
Appendix). In addition, the canopy gap age ranged from
1 to 40years, and the gap size ranged from 14 to 1600 m2.
2.3 Statistical analyses
e effects of canopy gap creation on soil carbon con-
tent and available nutrients were calculated by the nat-
ural log-transformed response ratio (lnRR) according
to Hedges etal. (1999):
lnRR =
ln
(
Y
t/
Y
c)=
lnY
t−
lnY
c
Fig. 1 Distribution of study sites included in this meta-analysis. The forest types are shown as colored dots
Page 4 of 23
Tongetal. Annals of Forest Science (2024) 81:12
where
Yt
and
Yc
are the means of variables in the canopy
gap treatment group and forest understory control group,
respectively. e variance (v) of each lnRR was calculated
as follows:
where
st
and
sc
are the SDs of variables in the canopy gap
treatment group and forest understory control group,
respectively;
nt
and
nc
are the sample sizes for the canopy
gap treatment group and forest understory control group,
respectively.
e meta-analysis was performed using OpenMEE
software (Wallace et al. 2017), which took the "study"
as a random factor to determine the mean effect size
of each variable. Confidence intervals (CI) of effect size
were calculated using the maximum likelihood (ML) ran-
dom-effect model. An effect of canopy gap treatment was
considered significant if the 95% CI did not overlap zero.
e overall effects of canopy gap creation on soil carbon
content and available nutrients were identified first. Sub-
sequently, subgroup analysis was conducted to evaluate
the response of soil carbon content and available nutri-
ents to canopy gap creation among different categorical
comparisons (sampling time, sampling location, or gap
characteristics). Higgins I2 statistics and the Q test were
used to quantify the heterogeneity degree (Qm) among
different studies. e random-effects model was used
for highly heterogeneous studies (I2 > 50% and p < 0.05)
rather than a fixed-effect model because it had the char-
acteristics of close weights among studies and extensive
applicability.
OpenMEE software offered the standard tools for
exploring publication bias, including ’fail-safe N’ (Rosen-
berg 2005) and funnel plots (Egger etal. 1997). If the fail-
safe number was higher than 5n + 10 (n represented the
number of paired observations in the analysis), it could be
concluded that the current result was robust and believ-
able. Funnel plots should be funnel-shaped and symmetri-
cally centered around the summary effect estimate of the
analysis in the absence of bias and heterogeneity. In this
study, it was suggested that no publication biases were
detected from our results, except for Cmic:Nmic (Table2 and
Fig.11 in Appendix). We used the forest plot to show the
results of this meta-analysis, and its generation was per-
formed using GraphPad Prism version 9.0.0 for Windows.
We utilized network visualization in Gephi software to
demonstrate significant correlations (Chen etal. 2019). In
this approach, variables in the dataset were represented
by network nodes, and pairwise conditional associa-
tions between variables were depicted by edges. Moreo-
ver, all network edges connected nodes that exceeded a
v
=
s
2
t
n
t
Y
t
2+
s
2
c
n
c
Y
c
2
predefined significant threshold calculated through Pear-
son correlation (p-value < 0.05).
e random-forest method was employed to identify
the primary predictors of the response ratios for carbon
content and nutrient availability. Concurrently, predicted
partial least squares path modeling (PLS-PM) was uti-
lized to analyze the impacts of biotic and abiotic factors on
changes in carbon content and nutrient availability result-
ing from gap opening. All the aforementioned data analy-
ses were conducted using R 4.0.2 (R Core Team, 2020).
3 Results
3.1 Mean canopy gap eects
Overall, canopy gaps increased soil moisture and soil tem-
perature but did not affect soil pH (Fig.2). Canopy gaps
had a negative effect on Corg and Nt but a positive effect on
Pt. For available nutrients, canopy gaps enhanced NH4+,
NO3−, and available P by 19.4%, 13.5%, and 17.3%, respec-
tively. Canopy gaps reduced the Ox-EEAs while having no
significant effect on the Hy-EEAs. Furthermore, canopy
gaps exhibited significant negative effects on Cmic, Nmic,
and Pmic, but a positive effect on Cmic:Nmic.
3.2 Factors inuencing thechanges induced bycanopy
gaps
We employed the subgroup analysis method to evaluate
the factors influencing canopy gap effects, as illustrated in
Figs.3 and 4. During the non-growing season, canopy gaps
exhibited a negative impact on soil pH. roughout both
the growing and non-growing seasons, canopy gaps led to
increased soil moisture and soil temperature. In the non-
growing season, canopy gaps negatively affected Corg and
Nt, whereas no effects were observed during the growing
season. In the growing season, the Pt, available P, NH4 +,
and NO3− were enhanced following gap creation. Canopy
gaps significantly reduced Ox-EEAs in both the grow-
ing and non-growing seasons, with no significant effect
observed on Hy-EEAs. In the growing season, canopy gaps
resulted in decreased Cmic and Nmic, and in the non-grow-
ing season, there were reductions in Nmic and Pmic. (Fig.3a).
Canopy gaps exerted a negative impact on soil pH in the
organic layer, while showing no effect in the mineral layer.
Canopy gaps increased the soil moisture by 7.6% and 15.9%
in the mineral and organic layers, respectively, and only
increased soil temperature by 5.1% in the mineral layer.
e Corg and Nt decreased while Pt increased in the mineral
layer due to gap opening. Canopy gaps notably enhanced
available P, NH4 +, and NO3− in the mineral layer but were
statistically insignificant in the organic layer. e Ox-EEAs
decreased in the mineral layer, and Hy-EEAs increased in
the organic layer following gap creation (Fig.3b).
Canopy gaps had a negative effect on soil pH at the
gap edge but not at the gap center. e soil moisture
Page 5 of 23
Tongetal. Annals of Forest Science (2024) 81:12
and temperature were enhanced at both the gap center
and edge following gap creation. Canopy gaps reduced
Corg and Nt at both the gap center and gap edge while
only enhanced Pt at the gap center. e NH4 + and NO3−
increased at the gap center, and the available P and NH4 +
increased at the gap edge following gap creation (Fig.3c).
Short and medium-term canopy gaps increased soil
moisture and soil temperature, whereas long-term can-
opy gaps exhibited diverse effects on them. Medium-term
and long-term canopy gaps reduced Corg and Nt, and the
short-term canopy gaps had no effect. Short-term canopy
gaps increased Pt. Short-term and long-term canopy gaps
increased available P and NO3−. Short-term, medium-
term, and long-term canopy gaps enhanced NH4 + by
16.0%, 10.5%, and 66.9%, respectively. Medium-term and
long-term canopy gaps reduced Cmic and Nmic, and long-
term canopy gaps had a negative effect on Pmic (Fig.4a).
Small and medium gaps decreased and increased the
soil pH, respectively, whereas large gaps had no effect.
Soil moisture and temperature notably increased while
Corg decreased in each gap size class. Small and large gaps
reduced Nt by 16.9% and 8.5%, respectively, and medium
gaps showed a positive effect on Pt. e NH4 + was
enhanced in each gap size class. e NO3− and available P
were enhanced in medium and small gaps, respectively. e
Ox-EEAs significantly reduced in small and medium gaps
but increased in large gaps. e Cmic decreased in large
gaps, and Nmic decreased in each gap size class (Fig.4b).
3.3 Correlations betweenthechanges insoil carbon
content andnutrient availability
e result of network analysis showed that changes in soil
moisture, Corg, Nt, NO3− and Cmic were the critical indica-
tors closely associated with most of the other soil physical,
chemical, and microbial properties (Fig. 5). Specifically,
the change in soil moisture was significantly and positively
related to the changes in Corg, Nt, available P, and NO3−,
and was negatively associated with the changes in NH4 +
and the Ox-EEAs. e change in Corg was significantly and
positively related to the changes in Nt, Pt, C:N, available P,
Fig. 2 Overall effects of canopy gaps on the SOC content and nutrient availability. Values are mean effect size (× 100%) ± 95% confidence intervals
(CI). The vertical line is drawn at lnRR = 0. The number of observations is within the parentheses. Corg, soil organic carbon; Nt, total nitrogen; Pt, total
phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available phosphorus, available P; Hy-EEAs,
hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic,
microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial biomass nitrogen
Page 6 of 23
Tongetal. Annals of Forest Science (2024) 81:12
and Nmic, and the most pronounced correlation was found
between changes in Corg and Nt. e changes in Nt and
Nmic were positively correlated. e change in NO3− was
negatively correlated with the change in Nt and NH4+. e
change in Pt was negatively correlated with the change in
Hy-EEAs. e changes in Hy-EEAs and Ox-EEAs were pos-
itively correlated. e change in Cmic was significantly and
positively correlated with the changes in Pmic and Cmic:Nmic.
3.4 Correlations betweenclimatic variables
andthechanges insoil properties
e changes in NH4 +, Hy-EEAs, Ox-EEAs, and Cmic
showed a positive correlation with MAT (Fig. 6a, c-e).
e change in available P decreased with increasing MAT
(Fig.6). e changes in Corg, available P, and Pmic decreased
with increasing MAP (Fig.6f-h). e changes in soil tem-
perature, Corg, Nt, and Ox-EEAs increased with increas-
ing UV radiation (Fig.6i-k, m). e change in available P,
Pmic, and Cmic:Nmic decreased with increasing UV radiation
(Fig.6l, n, o). e correlations between climatic variables
and the changes in soil carbon content and nutrient avail-
ability are detailed in Figs.13–15 in Appendix.
3.5 Key factors thatregulate thechanges insoil carbon
content andnutrient availability incanopy gaps
e random forest analysis suggested that the most
important factors associated with the change in Corg were
the changes in Nt and Nmic. e changes in Cmic, availa-
ble P, and Ox-EEAs were dominant factors regulating the
change in NH4+. e changes in Nmic, available P, and pH
were the dominant factors regulating the change in NO3−.
However, the importance of the changes in influencing
factors for Cmic and available P was relatively low (Fig.7).
e explanation of PLS-PM for the variance in the
response of soil carbon content was at the medium level
(GoF = 0.42). e PLS-PM showed that no correlation
was detected between climate (including mean annual
temperature (MAT) and UV radiation) and the change
in carbon content (including Corg). Climate negatively
affects the change in basic soil characteristics (includ-
ing soil moisture; path coefficient = -0.22, p < 0.05), while
positively affecting the change in total nutrients (includ-
ing Nt; path coefficient = 0.15, p < 0.05) and the change
in microbial characteristics (including Hy-EEAs and
Ox-EEAs; path coefficient = 0.23, p < 0.05). e change
in basic soil characteristics had no association with the
change in carbon content (path coefficient = 0.02, p > 0.05)
but positively affected the change in total nutrients (path
coefficient = 0.21, p < 0.05). e change in total nutrients
positively affected the change in carbon content (path
coefficient = 0.85, p < 0.05). e variance in the change in
carbon content was explained by 74% with climate and
changes in basic soil characteristics, total nutrients, and
microbial characteristics (Fig.8a).
Fig. 3 Response of SOC content and nutrient availability to canopy gap creation for two categorical variables, including sampling time, sampling
layer, and sampling location. Values are mean effect size (×100%) ± 95% confidence intervals (CI). The vertical line is drawn at lnRR=0. The number
of observations is within the parentheses. Corg, soil organic carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon
to total nitrogen; NH4+, ammonium; NO3-, nitrate; available phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs,
oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass
phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial biomass nitrogen
Page 7 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Otherwise, the explanation of PLS-PM for the variance
in the response of soil nutrient availability was at a rela-
tively low level (GoF = 0.17). No correlations were detected
between climate (including MAT and UV radiation) and the
changes in nutrient availability (including NH4+ and NO3−),
soil basic characteristics (including soil temperature), and
total nutrients (including C:N). Climate negatively affected
the change in microbial characteristics (including Pmic and
Hy-EEAs; path coefficient = -0.14, p < 0.05). e change in
total nutrients negatively affected the changes in microbial
characteristics (path coefficient = -0.18, p < 0.05) and nutri-
ent availability (path coefficient = -0.21, p < 0.05). e vari-
ance in the change in nutrient availability was explained by
just 7% with climate and changes in basic soil characteris-
tics, total nutrients, and microbial characteristics (Fig.8b).
4 Discussion
4.1 Canopy gaps reduced soil carbon content
Effectively mitigating climate change may be achieved
through the enhancement of forest carbon stocks resulting
from sustainable forest management (Huang etal. 2023).
Nevertheless, our results underscored a consistent reduc-
tion in both Corg and Cmic following gap creation, indicating
a potential decline in the soil carbon stock (Ni etal. 2016;
Amolikondori etal. 2020). In general, heightened levels of
irradiance and soil temperature resulting from gap creation
or forest thinning accelerated soil microbial activity, leading
to increased soil respiration and, consequently, enhanced
mineralization of soil organic matter and elevated surface
carbon efflux (Scharenbroch and Bockheim 2008) (Fig.9).
erefore, the distinct effects of gap formation and forest
thinning on soil carbon stock might be attributed to the
reduced initial carbon input, which could be potentially
caused by tree mortality during natural gap formation
and litter removal after selective logging. Nevertheless, it
is worth noting that the increased plant diversity resulting
from gap creation is likely to enhance soil carbon storage
over the long term (Degen etal. 2005; Lange etal. 2015;
Chen etal. 2018; Jia etal. 2021).
Corg is an integral component of the forest carbon pool,
and its active organic carbon fraction not only plays a crucial
role in the soil carbon turnover process but also serves as
a sensitive indicator of changes in climate conditions (Zhu
etal. 2020; Pravalie etal. 2021). Cmic plays a vital role in eco-
system functioning by serving as the supply and inventory of
effective soil nutrient resources (Singh and Gupta 2018; Li
etal. 2019). Our results showed that Corg and Cmic declined
significantly following gap creation, which might be
Fig. 4 Response of SOC content and nutrient availability to canopy gap creation for three categorical variables, including gap age and size.
Values are mean effect size (×100%) ± 95% confidence intervals (CI). The vertical line is drawn at lnRR=0. The number of observations
is within the parentheses. Corg, soil organic carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total
nitrogen; NH4+, ammonium; NO3-, nitrate; available phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs,
oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass
phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial biomass nitrogen
Page 8 of 23
Tongetal. Annals of Forest Science (2024) 81:12
attributed to the heightened mineralization of soil organic
matter mineralization brought by increasing soil microbial
activity. Furthermore, the diminished input of readily avail-
able carbon sources, such as root exudates, might result in
microbial carbon limitation, which was substantiated by our
discovery that Cmic:Nmic decreased significantly following
gap creation (Panchal etal. 2022). Nevertheless, despite the
absence of a significant correlation between the response of
Corg and Cmic to canopy gap disturbance, and the relatively
modest reduction in Cmic compared to Corg, several potential
factors may explain these observations. On the one hand,
the inadequate input of plant and microbial residues led to
a notable reduction in the Corg pool, thereby limiting the
favorable impact of warming on soil microbial respiration in
the warmed-up plots. On the other hand, microorganisms
adapted to the rising temperature in external environment
by producing enzymes with heightened thermal adaptation,
ultimately contributing to the gradual stabilization of the
microbial biomass pool.
Furthermore, we evaluated the effects of canopy gap
attributes and spatiotemporal factors on the response of
soil carbon content to canopy gap disturbance. Corg and
Cmic displayed consistent responses to canopy gap creation.
For instance, the results showed a remarkable reduction in
Corg and Cmic in medium-term (4–10years) and long-term
(> 10years) canopy gaps and no significant change in short-
term (≤ 3years) canopy gaps. ese differences might arise
from large amount of readily available carbon released
from the remaining litterfall induced by increased light and
temperature during the early stage of gap formation (Wang
etal. 2015, 2021). Notably, significant decreases in Corg and
Cmic occurred in the non-growing and growing seasons,
respectively. is result might be attributed to the lower
supplementation of root exudates during the non-growing
season. In contrast, soil microbial respiration maintained a
higher level in the growing season. Overall, the downward
trend in soil carbon stock following gap creation might
be attributed to variations in initial carbon input between
canopy gaps and forest understory sites.
4.2 Canopy gaps enhanced soil nutrient availability
e efficient recycling of nutrients plays a crucial role in
determining availability of nutrients in forest ecosystems.
Typically, natural disturbances or partial harvesting prac-
tices that expedite nutrient recycling through the creation
of canopy gaps also tend to enhance the spatial variability
Fig. 5 Network analysis for the correlation between soil physical, chemical, and microbial properties. Node colors are communities obtained
from the pre-classification; each community in the network is represented by the same node color. Node sizes are obtained from the ranking
degree, and wider nodes are the parentheses having more correlations with other parentheses. Red and green edge lines represent positive
and negative correlations, respectively. The edge thickness represents the strength of the correlation. Corg, soil organic carbon; Nt, total nitrogen;
Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available phosphorus, available P;
Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic,
microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial biomass nitrogen
Page 9 of 23
Tongetal. Annals of Forest Science (2024) 81:12
in soil nutrient availability (Prescott 2002; iel and Pera-
kis 2009; Xu etal. 2016). In the present study, there was a
notable improvement in soil nitrogen availability following
gap creation, as evidenced by a significant enhancement in
NH4+ and NO3− concentrations, consistent with the find-
ings from similar previous studies (iel and Perakis 2009;
Kucera etal. 2020). is result could be primarily attributed
to the reduction in nutrient uptake by vegetation, as well as
a decrease in carbon inputs from litter and root exudation,
which induced a decrease in nitrogen assimilation by soil
microbial biomass. Meanwhile, the increase in soil micro-
bial activity facilitated nitrogen mineralization from soil
microbial biomass, predominantly during the growing sea-
son and in the mineral layer.
e elevation of soil moisture levels had both negative
and positive effects on the subsequent increase in NH4+ and
NO3− following gap creation. is indicated that maintain-
ing an appropriate soil moisture level may accelerate soil
nitrification (Chen et al. 2015; Osborne etal. 2016). Fur-
thermore, our study revealed a significant enhancement in
NO3− concentration following gap creation. is suggested
that soil denitrification might decline and be primarily influ-
enced by soil moisture, temperature, and C:N (Bremner and
Shaw 1958; Elrys etal. 2021; Pan etal. 2022).
Our study detected a notable decrease in Nt and Nmic
following gap creation, with this decline becoming more
pronounced as gap age and size increased. is reduction
might be attributed to the decrease in organic nitrogen,
which severed as the primary nitrogen source of plants
and microorganisms through litter nutrient return and
root nutrient release. is, in turn, seemed to pose chal-
lenges in maintaining the soil nitrogen pool (Wu etal.
2022). Furthermore, our observations revealed a posi-
tive correlation between the changes in Nt and Nmic. is
implied that microbial biomass, acting as a source of bio-
available nitrogen, played a pivotal role in predicting the
spatiotemporal fluctuations within the soil nitrogen pool
(Miltner etal. 2012; Daly etal. 2021).
e primary source of phosphorus in forest soil is
derived from rock weathering (Kolowith and Berner
2002; Eger etal. 2018). We observed a noteworthy rise in
Pt following gap creation, a trend in line with other for-
estry practices, such as thinning (Tian etal. 2019; Zhou
et al. 2021). is increase might be attributed to the
improved soil temperature and moisture levels resulting
from gap creation, which in turn expedited the migra-
tion of phosphorus from the subsoil to the topsoil.
Meanwhile, a notable positive correlation was observed
Fig. 6 Relationships of mean annual temperature (MAT, a-e), mean annual precipitation (MAP, f–h), and mean ultraviolet radiation (UV radiation,
i-o) with response ratios (RR) of SOC content and nutrient availability. Fitted regressions and corresponding levels of significance are presented.
Corg, soil organic carbon; Nt, total nitrogen; NH4+, ammonium; available P, available phosphorus; Hy-EEAs, hydrolases-extracellular enzymes
activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Cmic:Nmic, the ratio of microbial biomass carbon
to microbial biomass nitrogen
Page 10 of 23
Tongetal. Annals of Forest Science (2024) 81:12
between enhancement of Pt and available P, indicat-
ing the crucial role of phosphorus migration in the soil
phosphate supply. e microbial biomass could serve as
a potential resource or reservoir of available plant nutri-
ents under specific environmental conditions (Singh etal.
1989; Wardle etal. 2004; Sugito et al. 2010). is study
observed a significant increase in available P and a simul-
taneous decrease in Pmic following gap creation. As men-
tioned earlier, the decrease in plant nutrient uptake might
contribute to the rise in available P. Simultaneously, the
insufficient substrate supply, resulting from reduced litter
nutrient return and root nutrient release, could lead to a
decline in microbial biomass. Additionally, the increased
soil moisture might enhance phosphorus availabil-
ity, likely achieved by promoting soil microbial activity
(Gomoryova etal. 2006; Yang etal. 2023).
Enzyme activity serves as a crucial indicator of soil bio-
logical activity and nutrient cycling in forest ecosystems,
with its alternation dependent on the initial soil nutrient
and water status (Gomez etal. 2020; Levakov etal. 2021).
is study observed a significant decline in Ox-EEAs fol-
lowing gap creation, potentially attributable to reduced
soil nutrient supply. Furthermore, the decrease in Ox-
EEAs exhibited a negative correlation with the increase
in soil moisture, suggesting improved soil moisture con-
ditions alleviated the reduction in soil enzyme activity.
Overall, soil available nutrients were enhanced following
gap creation, aligning with similar findings reported in
the literature regarding the impact of global forest recov-
ery on soil fertility (Zhou etal. 2022).
4.3 Eects ofclimate conditions onthechanges insoil
carbon content andnutrient availability
It is well-documented that changes in climate conditions
have far-reaching impacts on carbon sink and nutrient
cycling in forest ecosystems (Fung etal. 2005; Elrys etal.
Fig. 7 The random-forest analysis to identify the main predictors of the response ratios of SOC content (a, b) and nutrient availability (c, d, e). The
percent increase in mean squared errors (% IncMSE) represents the importance of main predictors, and negative values of % IncMSE, which indicate
a lack of importance, are not shown. MAT, mean annual air temperature; MAP, mean annual precipitation; Corg, soil organic carbon; Nt, total nitrogen;
Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available phosphorus, available P;
Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic,
microbial biomass nitrogen; Pmic microbial biomass phosphorus
Page 11 of 23
Tongetal. Annals of Forest Science (2024) 81:12
2021; Margalef et al. 2021). A recent study reported a
global reduction in the forest recovery effect on soil car-
bon sink and soil fertility due to joint changes in temper-
ature and rainfall (Zhou etal. 2022). In the present study,
we examined the influence of climate condition changes
on the dynamics of soil carbon content and available
nutrients following gap creation (Figs. 13, 14 and 15
in Appendix). e results indicated that temperature
generally attenuated the effects of canopy gaps on the soil
carbon content and available nutrients. Conversely, pre-
cipitation enhanced the canopy gap effects, aligning par-
tially with the findings of Zhou etal. (2022).
Specifically, our observations indicated that the ele-
vated MAP mitigated the decline in Corg and Pmic, as
well as the increase in available P (Fig.14 in Appendix).
ese findings suggested that heavy precipitation might
Fig. 8 Predicted partial least squares path modeling (PLS-PM) showing the effects of biotic and abiotic factors on the changes in SOC content
(a) and nutrient availability (b). In the structural model, the lines indicated paths, and the values adjacent to the lines denote the magnitude
of the path coefficients calculated by PLS regression. R2 values are shown for all endogenous latent variables. Values in the measurement model
represent the loadings between a latent variable and its indicators. The figure shows the final models after the model diagnosis processes.
Specifically, some of the changes in the regulating factors were removed because of low loading (|loading|< 0.70). The * denote significant
pathways (p < 0.05). The Pseudo Goodness-of-Fit (GoF) of model (a) and model (b) is 0.42 and 0.17, respectively. MAT, mean annual air temperature;
MAP, mean annual precipitation; Corg, soil organic carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total
nitrogen; NH4+, ammonium; NO3−, nitrate; available phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs,
oxidoreductases-extracellular enzymes activities; Cmic, microbial biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass
phosphorus
Fig. 9 Concept map of the potential mechanisms of SOC content and nutrient availability in response to canopy gap creation. Corg, soil organic
carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available
phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic,
microbial biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon
to microbial biomass nitrogen
Page 12 of 23
Tongetal. Annals of Forest Science (2024) 81:12
have constrained both soil microbial respiration and the
transformation of Pmic into available P. e rise in MAT
intensified the decrease in Cmic (Fig. 13 in Appendix).
is phenomenon might be attributed to the carbon
losses in the soil induced by warming, as explained by the
mechanism of substrate depletion (Walker etal. 2018). In
addition, the elevated MAT also amplified the increase
in NH4+, possibly due to the plant exhibiting heightened
nutrient uptake at elevated temperatures.
Solar radiation is intricately linked to plant photosyn-
thesis and nutrient stoichiometry, garnering heightened
attention for its impact on biogeochemical cycling in recent
studies (Epp etal. 2007; Ji etal. 2020; Barnes etal. 2023). In
the current investigation, we evaluated the influence of UV
radiation on the dynamics of both the physical and chemi-
cal properties of the soil following gap creation (Fig.15 in
Appendix). Previous studies have consistently demon-
strated that the formation of canopy gaps significantly ele-
vates soil temperature, primarily due to the increased solar
radiation reaching the forest floor (Wang etal. 2022). Our
study further observed a pronounced enhancement in soil
temperature caused by UV radiation, potentially resulting
in a more substantial impact on soil microbial respiration.
We observed that UV radiation enhanced the nega-
tive effects of canopy gaps on Corg and Nt, possibly due
to an enhancement in soil microbial respiration. Like-
wise, our findings revealed that UV radiation facilitated
a reduction in Ox-EEAs by instigating substantial losses
in soil organic matter. In contrast, it was observed that
UV radiation reduced the positive effects of canopy gaps
on available P, as well as the negative effects on Pmic, sug-
gesting that UV radiation might play a crucial role in
regulating phosphorus cycling through the modulation
of soil phosphorus-related enzyme activities, such as soil
acid phosphatase. Meanwhile, we found that the increase
in Cmic:Nmic was negatively associated with UV radiation,
implying that high solar radiation could mitigate micro-
bial nitrogen limitation to some extent.
4.4 Study limitations andmanagement implications
While we have endeavored to offer a comprehensive
understanding of the effects of canopy gaps on soil car-
bon content and nutrient availability through a global
meta-analysis, there remain several potential limita-
tions. Firstly, the sampled studies do not encompass the
full spectrum of global forests, focusing primarily on
eastern forests. erefore, further research spanning a
broader range of forest biomes, especially boreal and
tropical forests, is imperative to ascertain the general-
ity of our findings. Secondly, the analysis overlooks vital
information regarding the surrounding gaps of trees. For
example, tree height correlates with the angle of incom-
ing solar radiation, and the crown radius is associated
with gap edge effect. irdly, this study lacks direct evi-
dence to elucidate potential mechanisms, particularly
the responses of soil microorganisms after gap creation.
Finally, previous research confirms the close association
between biodiversity and soil nutrient availability. How-
ever, information regarding the variation in the gap-mak-
ing species is not recorded in the present meta-analysis.
Our study has significant implications for sustainable
forest management. Firstly, it highlights the pronounced
effects of canopy gaps on the soil carbon sequestra-
tion, nutrient availability, and their interconnectedness
with climate conditions. Consequently, integrating the
canopy gap effect into spatially explicit models is crucial
for achieving a comprehensive understanding of carbon
sequestration and biodiversity conservation (O’Connor
2008; Forsius etal. 2021). Secondly, this study has signifi-
cantly contributed to a comprehensive understanding of
the effects of canopy gaps on soil carbon and nutrients.
is, in turn, facilitates more accurate predictions of for-
est succession in the future. With the growing popularity
of close-to-nature forest management, the implementa-
tion of small-scale harvests and artificial canopy gaps is
poised to play crucial roles in restoration of low-quality
secondary forests and monoculture plantations (Fig. 16
in Appendix). irdly, prior studies have emphasized the
necessity of sustainable forest management for climate
change adaptation (Canadell and Raupach 2008; Liu etal.
2013; Keenan 2015). Our study contributes valuable infor-
mation regarding the impacts of changes in climate condi-
tions on soil carbon content and nutrient availability after
the creation of canopy gaps. is information is crucial
for the implementation of artificial canopy gaps in forest
management under current and future climate conditions.
5 Conclusions
e occurrence of canopy gaps was found to decrease soil
carbon content while simultaneously increasing nutrient
availability in the topsoil layer of forest ecosystems. ese
changes became more pronounced with the age and size of
canopy gaps. e alteration in soil moisture level following
gap creation might serve as a crucial driver of the response
of soil carbon pool and nutrient availability. Precipita-
tion and temperature played negative and positive roles,
respectively, in influencing the soil carbon content and
nutrient availability. Additionally, UV radiation exhibited
a positive regulatory effect on the response of soil carbon
and nitrogen components, while playing a negative regu-
latory role in the response of phosphorus components.
In summary, this study sheds light on the significant roles
played by canopy gaps in regulating carbon stock dynamics
and nutrient biogeochemical cycles in forest ecosystems.
e findings have noteworthy implications for ecological
restoration and fine-scale regulation of forest structure.
Page 13 of 23
Tongetal. Annals of Forest Science (2024) 81:12
6 Appendix
Text 1. List of the 52 papers from which the data were
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Fig. 10 The PICOS process of this meta-analysis
Page 16 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Fig. 11 Funnel plot for the 16 variables
Fig. 12 Frequency of the division in gap age (a) and size (b)
Page 17 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Fig. 13 Relationships of mean annual temperature (MAT, a-p) with response ratios (RR) of SOC content and nutrient availability. Corg, soil organic
carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available
phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial
biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial
biomass nitrogen
Page 18 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Fig. 14 Relationships of mean annual precipitation (MAP, a-p) with response ratios (RR) of SOC content and nutrient availability. Corg, soil organic
carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available
phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial
biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial
biomass nitrogen
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Tongetal. Annals of Forest Science (2024) 81:12
Fig. 15 Relationships of mean ultraviolet radiation (UV radiation, a-p) with response ratios (RR) of SOC content and nutrient availability. Corg, soil
organic carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+, ammonium; NO3−, nitrate; available
phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular enzymes activities; Cmic, microbial
biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial biomass carbon to microbial
biomass nitrogen
Page 20 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Fig. 16 Response of SOC content and nutrient availability to canopy gap creation for two categorical variables, including forest type and gap
formation type. Values are mean effect size (× 100%) ± 95% confidence intervals (CI). The vertical line is drawn at lnRR = 0. The number of observations
is within the parentheses. Corg, soil organic carbon; Nt, total nitrogen; Pt, total phosphorus; C:N, the ratio of soil organic carbon to total nitrogen; NH4+,
ammonium; NO3−, nitrate; available phosphorus, available P; Hy-EEAs, hydrolases-extracellular enzymes activities; Ox-EEAs, oxidoreductases-extracellular
enzymes activities; Cmic, microbial biomass carbon; Nmic, microbial biomass nitrogen; Pmic microbial biomass phosphorus; Cmic:Nmic, the ratio of microbial
biomass carbon to microbial biomass nitrogen
Table 1 Correlation analysis of geographical and climatic variables. MAT, mean annual temperature; MAP, mean annual precipitation;
UV radiation, ultraviolet radiation
Latitude Longitude Elevation MAT MAP
Longitude -0.313** 1
Elevation - - 1
MAT -0.598** - - 1
MAP -0.418** - - 0.454** 1
UV radiation -0.972** 0.328* - 0.599** 0.403**
* p < 0.05; ** p < 0.01
Table 2 Description of the Fail-safe N for the 16 variables
Sample size (n) Fail-safe N Sample size(n) Fail-safe N
pH 192 2596 NO3−178 233,147
Soil M 199 18,852 Available P 100 389,209
Soil T 117 35,450 Hy-EEAs 87 1992
Corg 303 5042 Ox-EEAs 23 427
Nt238 23,171 Cmic 128 638
Pt96 3052 Nmic 58 667
C:N 147 1553 Pmic 68 1590
NH4+179 83,308 Cmic:Nmic 22 0*
Page 21 of 23
Tongetal. Annals of Forest Science (2024) 81:12
Acknowledgements
We sincerely thank all the scientists whose data and work were included in
this meta-analysis.
Code availability
Not applicable.
Authors’ contributions
R T and TG W designed the study, provided the funding and revised the manu-
script; R T, BY J, and GG W performed the experiments, data collection, and
drafted the manuscript; CY L, C M performed data processing and statistics; NF
Z and WW Y performed part of the experiment. All authors read and approved
the final manuscript.
Funding
This work was supported by the Fundamental Research Funds for the
Central Non-profit Research Institution of Chinese Academy of Forestry
(CAFYBB2022SY010), and Pioneer and Leading Goose R&D Program of Zheji-
ang (2022C02053).
Fundamental Research Funds for the Central Non-profit Research Institution of
Chinese Academy of Forestry,CAFYBB2022SY010,Ran Tong,Pioneer and Lead-
ing Goose R and;D Program of Zhejiang, 2022C02053, Tonggui Wu
Availability of data and materials
The datasets generated and/or analyzed during the current study are available
in the Figshare repository at https:// doi. org/ 10. 6084/ m9. figsh are. 24038 883. v3.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 East China Coastal Forest Ecosystem Long-Term Research Station, Research
Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou,
Zhejiang 311400, People’s Republic of China. 2 Zhejiang Forest Resource
Monitoring Center, No. 71 East Fengqi Road, Hangzhou 310020, China.
3 Department of Forestry and Environment Conservation, Clemson University,
Clemson SC29634-0317, USA.
Received: 25 May 2023 Accepted: 12 February 2024
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