First Approach of Abiotic Drivers of Soil CO 2 Efflux in Barro Colorado Island,Panama

Abstract

Soil CO₂ fluxes from tropical forests into the atmosphere are expected to increase due to global warming. Studies of environmental conditions that contribute to carbon flux are now an important focus for climate change research. However, carbon flux in tropical areas such as Panama has received less attention. In Panama, water sources, rainforests, and soil conditions are vital natural resources, particularly within the Panama Canal watershed. Mature and secondary forests represent around 60% of Panama land cover. Secondary forests are considered potential carbon sinks and they are of economic interest as a means of mitigating increasing anthropogenic CO₂ emissions; however, the dynamics of carbon fluxes in the soil of secondary forests remain poorly understood. This research investigated which environmental factors influence soil CO₂ efflux. We used a closed chamber method to measure soil CO₂ in the tropical forest of Barro Colorado Island, Panama. During 2016 to 2017, humidity had a significant effect on CO₂ flux (average: 4.36 μmol/m²s), which was substantially lower than expected for this type of tropical forest. These findings will contribute to a better understanding of the complex and dynamic interrelationships between the water and carbon cycle, as well as abiotic drivers of soil CO₂ fluxes. Our use of soil respiration chambers and infrared gas analyzer systems represents an innovative contribution to the water-carbon nexus of Panama and potentially of other countries.

Keywords

Barro Colorado Island closed soil respiration chamber efflux soil respiration

Introduction

CO₂ represents 60% of total global greenhouse gas (GHG) emissions¹; its increased levels in the atmosphere are mainly related to human activity. Soils act as sources and sinks for GHGs such as methane, CO₂, and nitrous oxide.² Although CO₂ storage may be an effective method for mitigating its effects on climate, exact quantification of CO₂ emissions is required to determine appropriate strategies to address-related land-use management and global climate change issues.³

The mitigation of CO₂ emissions is essential for decreasing the impact of climate change in the coming decades.^4,5 In particular, developing countries with extensive green areas have been encouraged to contribute to climate change mitigation efforts through conservation, management, and forest expansion.⁶ Deforestation is the second leading source of anthropogenic CO₂ emissions, after fossil fuel combustion.⁷ Fossil fuels represent 6% to 17% of global anthropogenic CO₂ emissions into the atmosphere.^8,9 Panama is among the countries with the greatest natural diversity in the world. Varied evergreen and deciduous forests dominate the Panamanian landscape and are broken up by mangrove swamps, grasslands, crops, and scrub. From 1950 to 2000, Panama lost 30% of its forest cover due to settlement expansion and growth of the national transportation network. In the past 20 years, the deforestation rate has slowed due to the implementation of environmental regulations, respect for indigenous areas, and reforestation in uninhibited agricultural plots.¹⁰

Carbon stocks in tropical forests include aerial and subterranean biomass.¹¹ The natural release of CO₂ into the atmosphere from tropical forests occurs through respiration in aerial and underground biomass.¹² Heterotrophic respiration occurs via macro- and microinvertebrates in the soil.¹³ When forest areas are cleared, carbon stored above- and belowground in leaves, branches, stems, and roots is released in various ways such as combustion, vegetable matter decomposition, and soil carbon accumulation,¹⁴ thus contributing to greenhouse gas emissions.¹⁵

The assessment of CO₂ stocks and net CO₂ capture is of crucial importance for determining whether a forest acts as a carbon sink or source. This knowledge is important for establishing a link between carbon sequestration and carbon neutrality, a frequent goal for energy policy.¹⁶ Reclaimed mine soils can be used to sequester carbon. The CO₂ sequestration potential of an 11-year-old reclaimed mine afforested with fast-growing trees was compared with that of the Sal forest as a reference; the results showed that annual soil CO₂ flux was higher in forest soil (53.7 t CO₂ ha⁻¹ y⁻¹) than in reclaimed soil (33.3 t CO₂ ha⁻¹ y⁻¹), demonstrating that forest reclamation of postmining land increases its potential as a terrestrial C sink and reduces CO₂ levels.¹⁷ Currently, manufacturing, transportation, and local industry produce nearly 10 Gt of carbon to the atmosphere annually, with no expectation of a substantial imminent decrease in these emission rates. Therefore, the sequestration of atmospheric CO₂ as organic carbon in the biosphere is a topic of interest to stem the rate of GHG increase and associated changes to our climate.¹⁸

Ecosystem CO₂ emissions are mainly produced through respiration; therefore, this process influences the net productivity of the ecosystem.^19,20 On a global scale, the total mass of carbon stored in soil is 1576 Pg, of which 32% is found in the tropics. Carbon storage is lost mainly through changes in land use. With increased deforestation, carbon loss is expected to increase²¹; therefore, soil carbon is considered to be more important than carbon stored in aerial biomass.²² In Panama, soil carbon is not linked with common predictors used in models, such as plant biomass or litter production; one fundamental equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor has been used to predict nearly 50% of the variation in tropical soil carbon stocks, indicating a robust indirect effects of base cation accessibility on tropical soil carbon storage.²³

Organic carbon in soil varies temporally and spatially; however, data are scarce and unrepresentative of tropical areas.²⁴ Soil is a complicated medium consisting of organic and mineral aggregate particles containing microorganisms that perform a diversity of physiological processes.²⁵ Soil properties vary spatially and temporally in all directions.²⁶ Soil erosion processes other than surface runoff and sediment transport have significant effects on soil organic carbon transport and loss along slopes.²⁷ Soil organic carbon variation across a landscape can determine differences in soil fertility and plant vigor.

CO₂ flux is the result of several processes including underground biomass respiration by macro- and microorganisms, and CO₂ production and transportation through soil.²⁸ CO₂ flux is also influenced by environmental factors such as temperature, moisture, and soil properties.²⁹ In arid Patagonian ecosystems, seasonal differences in soil respiration are affected mainly by the interaction between soil temperature and water content.³⁰ In response to soil warming, manure application, and soil salinity, CO₂ flux values were higher at high soil temperatures than at low soil temperature.³¹ The transport of soil CO₂ to the surface has been found to be affected by diffusion, convection, and mass flow in the gaseous and liquid states.³² Diffusion is thought to be the most important process influencing CO₂ flux in the gas phase, controlled by the CO₂ concentration gradient³³ in a manner similar to that of mass flow by pressure fluctuations in surface soil.^34,35

In forest soils, CO₂ is produced from respiration by autotrophic roots and heterotrophic microbes, related rhizosphere bacteria, and fungi living in organic and mineral soil, and also by soil faunal activity.³⁶ The activity of soil heterotrophic organisms is comparable with the decay of soil carbon, and CO₂ exuded from roots and the rhizosphere is linked to that produced by aboveground plant tissues.³⁷ The contribution of CO₂ from the soil to the atmosphere in a tropical forest can be quantified by surface soil CO₂ flux measurements.

Rainforest soils are important natural resources in Panama, particularly in the Panama Canal watershed. Mature and secondary forests represent around 60% of the land cover of Panama. Secondary forests, which are considered potential carbon sinks, are of great economic interest due to their low inversion and large potential contribution to mitigating increasing anthropogenic CO₂ emissions. Therefore, in this study, we examined the influence of environmental factors on soil CO₂ efflux on Barro Colorado Island using a closed chamber soil CO₂ measurement method.

Materials and Methods

Study site

This study was conducted on a 1 ha plot within the Ava research area (Figure 1), which was named for its Barro Colorado Island soil class, on Barro Colorado Island, Panama (9°9′N, 79°51′W). Barro Colorado Island is a unique ecosystem within an international waterway that was formed as a result of construction of the Panama Canal. Its forests are mainly secondary and primary forest. The soil at the study site mainly consists of Luvic, Alumic, Lixic, and Acric soils.³⁸ The island extends over an area of 1500 ha and has an altitude of about 137 m above Gatun Lake.³⁹

Figure 1.

Map of Barro Colorado Island located within Gatun Lake. Trails and research sites are indicated. The Ava research site is a 6 ha plot used the Smithsonian Tropical Research Institute (STRI) for carbon quantification research projects.

Soil is a complex medium that varies spatially. The soils on the island are generally less than 50 cm deep and rich in clay,⁴⁰ with soils deeper than 1 m on flat peaks. The island contains 2 formations of fossiliferous sedimentary rock, the Bohío and Caimito formations.⁴⁰ The soils of Barro Colorado Island differ from those of other wet tropical forests in that they develop on kanditic clay minerals through intermediate smectites, rather than via allophane and halloysite.⁴⁰ These widely distributed aluminum-saturated smectitic soils are theoretically unbalanced and make Barro Colorado Island soils distinct. Although texturally uniform, these soils are physically mutable in terms of water source, root ventilation, and site stability. Stoichiometric differences in soils among Asian tropical forests have shown that Barro Colorado Island soils are moderately rich in Ca and Mg, but not in K.⁴¹ Figure 2A to C shows our research site on the island and the equipment used for the study.

Figure 2.

Research site in a 1 ha plot: (A) main eddy tower, (B) equipment used in this study, (C) soil gas flux chamber, (D) meteorological station called at El Claro, and (E) daily accumulated rainfall (mm) from January 2016 to January 2018. The rainy and dry seasons are evident from patterns in the data.

The climate of the island is typical of a tropical lowland forest, with an average temperature of 27°C; the rainy season extends from May to December and the dry season from mid-December to April. The average annual rainfall is 2642 (±566) mm.⁴² The island is enclosed by a semi-deciduous, mixed-age rain forest, mainly comprising 2 abundant free-standing fig species (Ficus insipida and Ficus yoponensis) as a result of past settlement.⁴³

Barro Colorado Island was an agricultural site for at least 6000 to 7000 years,^44,45 and most areas have been deforested at some point during the past 1000 years. In the 1920s, agriculture on the island was abandoned and it was made a natural reserve, with a field station was established for tropical studies.^46,47 Currently, the island supports about 100 people including staff scientists, administrative personal, and visitors.

CO₂ flux in soil

In April 2016, an automated gas flux system (LI-8100A; LI-COR Biosciences, Lincoln, NE, USA) was installed on Barro Colorado Island. The system continuously measures long-term CO₂ flux in soil; it consists of closed dynamic automated chambers, a multiplexer, and a closed-loop infrared gas analyzer.⁴²

Four polyvinyl chloride collars were buried at a shallow depth at selected measurement sites. Chambers with an external diameter of 20 cm were installed on the collars at the vertices of a 20 m × 20 m square centered radially to a microclimatic tower linked to an electrical network. CO₂ flux measurements are taken every second for 2 minutes after the chamber was closed. A pre-purge of 30 seconds and post-purge of 45 seconds were performed to ensure that the system was cleaned between measurements.^34,42

During each measurement, a small portion of the air in the chamber was pumped to the infrared gas analyzer to determine the CO₂ concentration. The system software calculated the CO₂ flux results according to the rate of change in gas concentration over time within the chamber, as well as other parameters. We performed regression analyses and based on R², adjusted the values using an exponential or linear equation.³⁴ All recorded data were included except for those collected by chamber 4 because it was impacted by a fallen branch, rendering it unusable.

Soil temperature and humidity

Soil temperature and humidity data were recorded by the Smithsonian Tropical Research Institute (STRI; https://biogeodb.stri.si.edu/physical_monitoring/research/barrocolorado) at the Ava study site near the microclimatic tower for the period from January 2016 to November 2017, using procedures described in detail below.

Temperature

In January 2016, 2 floor thermistors 10.4 cm long (Model 107; Campbell Scientific, Logan, UT, USA) were permanently installed, and data were recorded using a datalogger (CR1000; Campbell Scientific) in 5-minute intervals. Soil temperatures were measured continuously near the chambers using 4 thermistors 6 cm long (model 8150–203; LI-COR) that functioned in combination with the chambers.

Humidity

Soil moisture was monitored using 3 time-domain reflectometers (TDRs; CS616; Campbell Scientific) vertically inserted into the soil near the chamber system.⁴² Soil moisture measurements were taken continuously throughout the study period.

Rainfall

Rainfall was recorded in the El Claro region of Barro Colorado Island (Figure 2C, D). The measurement area was surrounded by trees above 20 m in height. Rainfall was recorded using a tipping rain gauge (model TB3; Hydrological Services) that collected data every 5 minutes throughout the study period. The duration and peaks of the rainy seasons in 2016 and 2017 are shown in Figure 2B.

Statistical analysis

We analyzed variation in soil temperature, humidity, precipitation, and CO₂ flux using the coefficient of variation and standard deviation (SD). Linear regression was performed to examine the relationships among abiotic factors and CO₂ flux during the dry and rainy seasons of 2016 and 2017, using Pearson product correlation coefficient (r) as an index of the covariation between 2 known linearly related quantitative variables.^48,49 We calculated r as follows:

r = \frac{\sum^{} (x - \bar{x}) (y - \bar{y})}{\sqrt{\sum^{} {(x - \bar{x})}^{2} \sum^{} {(y - \bar{y})}^{2}}}

(1)

where $\bar{x}$ is the arithmetic mean of x and $\bar{y}$ is that of y.⁴⁸ We normalized r dividing the covariance by the SD of each variable. We further used the determination coefficient (R²) to evaluate the amount of variation in one variable that is shared by another variable.⁴⁸

We tested the normality of the CO₂ flux data using the Kolmogorov-Smirnov (K-S) test,⁵⁰ which does not require pooling of the data and works for small samples. For a random sample of size n from the distribution of random variable x, divided into k classes, the K-S statistic D_n was calculated as follows:

D_{n} = \max_{x} | S_{n} (x) - F_{0} (x) |

(2)

S_{n} (x) = {\begin{matrix} 0 & x < x_{(1)} \\ \frac{k}{n} & x_{k} \leq x < x_{(x + 1)} \\ 1 & x \geq x_{n} \end{matrix}

(3)

where S_n is the proportion of sample values that are equal to or less than x.

Because the data did not follow a normal distribution, we compared means using the nonparametric Mann-Whitney U test,⁵⁰ where U was calculated as follows for a random variable R₁ and of the sample sizes n₁ and n₂:

U = n_{1} n_{2} + \frac{n_{1} (n_{1} + 1)}{2} - R_{1}

(4)

Results

In the first quarter of 2016, Panama was experiencing a strong El Niño phenomenon that had begun in 2014. Rainfall frequency and intensity was lower on Barro Colorado Island during this period, which ended in May 2016.⁵¹ In 2017, the island experienced a neutral El Niño year, which was accompanied by increased rainfall throughout the Central Caribbean region.⁵²

CO₂ soil flux

Between April 2016 and January 2018, the minimum and maximum CO₂ flux values were 1.11 and 8.40 μmol/m²s, respectively (average ± SD = 4.36 ± 1.62 μmol/m²s), with a coefficient of variation of 37.1% (Table 1 and Figure 3). Measuring chamber 1 measured lower CO₂ flux values than chambers 2 and 3. There was less variability between chambers 2 and 3 (SD = 1.42). Spatial variability between chambers may have been due to the composition and structure of the forest floor and the distribution of tree roots near the chambers. We observed no pattern among the average CO₂ flux values of the chambers, despite an apparent decrease within each chamber as the rainy season progressed (Figures 4 and 5). CO₂ flux differed between the dry (4.62 μmol/m²s) and rainy (5.15 μmol/m²s) seasons during 2016 to 2018 (Mann-Whitney U test, n = 63 for each season, P < .0005).

Table 1.

CO₂ flux data collection period for each of the 4 measurement chambers. ✕: Data not recorded. ✓: Data recorded.

Chamber	May-August 2016	September 2016	October 2016	January-May 2017	August 2017	January 2018
1	✕	✓	✓	✓	✓	✓
2	✕	✓	✕	✓	✓	✓
3	✕	✓	✕	✓	✓	✓
4	✕	✓	✕	✕	✕	✕

Figure 3.

Photographs of the soil gas flux chambers used in this study: (A) infrared gas analyzer (IRGA) multiplexer device with chambers 1 and 2, (B) chambers 2 and 3, and (C) chamber 4.

Figure 4.

Soil CO₂ efflux data (μmol/m²s) collected by chambers 1, 2, and 3 at the Ava site from April 2016 to January 2018.

Figure 5.

Soil CO₂ efflux data (μmol/m²s) collected by chambers 1, 2, and 3 at the Ava site from April 2016 to January 2018.

We performed separate linear regressions to examine the relationships between CO₂ flux and 3 environmental factors: soil temperature, soil moisture, and rainfall. The R² values are listed in Table 2. Then, we performed multiple regression analyses of the same factors in the dry and rainy seasons of 2016 and 2017 (Table 3). In 2017, the relationships between CO₂ flux and the environmental factors were positive in both seasons. Temperature had the strongest relationship with CO₂ flux during the dry season (R² = .33). Soil moisture was the most significant environmental factor during the rainy season (R² = .46). However, none of the R² values were greater than .5.

Table 2.

Determination coefficients (R²) for linear regressions of CO₂ flux with 3 environmental factors.

Factor	R ²
Factor	2016-2017	Dry season 2016	Rainy season 2016	Dry season 2017	Rainy season 2017
Soil temperature	.00	.01	.09	.33	.13
Soil humidity	.09	.65	.10	.00	.46
Rainfall	.03	.00	.04	.05	.05

Table 3.

Determination coefficients (R²) for multiple linear regressions of CO₂ flux with 3 environmental factors included and excluded (2016-2017).

Factor	R ²
Factor	Included	Excluded
Soil temperature	.37	.03
Soil humidity	.41	.01
Rainfall	.06	.02

Soil temperature

Soil temperature was measured using a single thermistor from January 21, 2016 to November 18, 2017. The maximum and minimum temperatures were 27.5°C and 22.9°C (average = 25.4 ± 0.69°C), with a coefficient of variation of 2.7% (Figure 6). Soil temperatures decreased during the rainy season and increased during the dry season.

Figure 6.

Soil temperature data (°C) collected from April 2016 to November 2017.

Soil humidity

Soil moisture was measured using a single TDR at a depth of 100 cm; measurements were adjusted using a polynomial equation. The maximum and minimum soil moisture values were 0.73 and 0.25 cm³/cm³ (average = 0.41 ± 0.9 cm³/cm³), with a coefficient of variation of 21.30% (Figure 7). Soil moisture increased during the rainy season and decreased during the dry season. Similar patterns were observed in both 2016 and 2017; humidity was generally higher in 2016.

Figure 7.

Soil moisture data (cm³/cm³) collected from January 2016 to November 2017.

Rainfall

Rainfall was measured from January 2016 to January 2018. The maximum and minimum cumulative daily rainfall values were 146.3 and 0.3 mm (average = 11.4 ± 18.1 mm), with a coefficient of variation of 155.15%. In 2016, soil moisture had the highest positive correlation with CO₂ flux in both the dry season (R² = .65) and the rainy season (R² = .10).

Discussion

Temperature and rainfall did not appear to directly influence the loss of carbon through soil CO₂ flux throughout the 2016 to 2018 study period; however, analyses of 2017 alone showed different results. A longer-term study is necessary to better identify seasonal and spatial variability in soil CO₂ flux in this region. Similarly, we did not detect conclusive patterns in soil CO₂ flux in relation to the factors examined in this study. It is necessary to analyze other soil physical variables to determine the role of these factors in soil CO₂ flux dynamics, as well as changes in rainfall and temperature patterns.

We found that variation in soil temperature had a positive relationship with that in soil CO₂ flux during the dry period in 2017. Increases in soil moisture do not always lead to an increase in soil CO₂ production or concentration.⁵³ In this study, soil moisture variation was more strongly positively correlated with CO₂ flux in the rainy season of 2017 than during the entire study period of 2016 to 2018. Thus, soil moisture appears to play a greater role in CO₂ flux variation than soil temperature.

Soil CO₂ flux was considerably lower during months with relatively high rainfall; however, during the transition from the dry season to the rainy season, it increased. This is consistent with previous findings that decreases in rainfall generally increase soil CO₂ flux.⁵⁴ It has been suggested that increased temperature and rainfall due to global climate change will increase soil CO₂ flux in the future.⁵⁵

In a previous study, soil respiration was measured every 3 hours at each sample site for a period of 48 hours each on sunny days in the rainy and dry seasons, using an ultra-portable gas analyzer and soil gas flux systems; the results confirmed the need for long-term measurements.⁵⁶ In a sparse furrow-irrigated vineyard, an automatic CO₂ exchange system equipped with a transparent soil chamber and infrared gas analyzer was used to assess the spatiotemporal variability in soil respiration due to abiotic and biotic factors, which were found to depend on soil temperature via canopy structure, with irrigation-dependent soil moisture playing a secondary role in regulating soil respiration.⁵⁷

A meta-analysis of the temperature sensitivity (Q₁₀) of soil respiration and potential controls of climate factors, soil properties, and vegetation characteristics across biomes at the global scale used a dataset including 658 groups of Q₁₀ values and relevant environmental factors from 226 articles published before February 2018 and found that several environmental conditions affected these measurements under conditions similar to those of this study.⁵⁸

In soil science studies, it is important to consider soil-specific parameters at different spatiotemporal scales.^59-61 In this study, certain factors were expected to greatly influence soil respiration, including abiotic factors such as weather and soil texture; however, longer-term measurements should be collected, over periods of at least 2 or 3 years.

The contributions of urban land use to ambient air quality were examined in Bahir Dar and Hawassa cities of Ethiopia using data collected daily with a portable gas monitor with attached temperature and relative humidity sensor and a handheld multigas detector; elevated levels of CO, CO₂, and volatile organic compounds were detected in the atmosphere and found to have a significant impact on the terrestrial ecosystem and global warming.⁶²

Conclusions

During April 2016 to January 2018, we examined soil CO₂ flux on Isla Barro Colorado, Panama, using 4 closed soil gas flux chambers. The average CO₂ flux during the study period was 4.36 μmol/m²s, which was surprisingly low for this type of tropical forest. We did not identify significant flux patterns in response to environmental factors during the dry and rainy seasons of 2017. Rain, soil moisture, and soil temperature were positively correlated with seasonal variation in CO₂ flux; the strongest relationships were with temperature overall, and soil moisture during the rainy season. We concluded that soil moisture played a more important role in soil CO₂ flux throughout the 2016 to 2018 study period. The results of this study show that CO₂ fluxes at ground level are an important source of atmospheric CO₂. A longer-term study is required to determine whether environmental factors play a significant role in seasonal CO₂ flux patterns over time.

Footnotes

Acknowledgements

We thank the editor and reviewers for their time and constructive comments, which have helped improve our manuscript. We also thank Dr M. Detto for sharing his data, and the personnel of the El Centro de Investigaciones Hidráulicas e Hidrotécnicas (CIHH) of the Universidad Tecnológica de Panamá for their assistance.

Funding:

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study (project no. INF2010-025) was supported by funding from the Sistema Nacional de Investigación (SNI) and Secretaría Nacional de Investigación e Innovación to R.P.

Declaration of conflicting interests:

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Contributions

LS and RP conceived and designed the experiments and performed and interpreted the data analyses. LS wrote the first draft of the manuscript and RP made critical revisions and contributed to the final manuscript. All authors reviewed and approved the final manuscript.

ORCID iD

Reinhardt Pinzón

References

Intergovernmental Panel on Climate Change (IPCC). Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C Above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty; 2018. https://www.ipcc.ch/sr15/.

Vargas

Barba

Greenhouse gas fluxes from tree stems. Trends Plant Sci. 2019;24:296-299.

Oertel

Matschullat

Zurbaa

Zimmermanna

Erasmi

Greenhouse gas emissions from soils: a review. Chemie der Erde. 2016;76:327-352. doi:10.1016/j.chemer.2016.04.002.

Aichele

Felbermayr

Kyoto and the carbon footprint of nations. J Environ Econom Manage. 2012;63:336-354. doi:10.1016/j.jeem.2011.10.005.

Delucchi

MA.

Impact of biofuels on climate change, water use, and land use. Annals of the New York Academy of Sciences. 2010;1195:28-45. doi:10.1111/j.1749-6632.2010.05457.x, 2010.

United Nations. Protocolo de Kioto de la convención marco de las naciones unidas sobre el cambio climático; 1998. https://unfccc.int/resource/docs/convkp/kpspan.pdf.

Van der Werf

Morton

DeFries

Oliver

Kasibhatla

Jackson

, et al. CO2 emissions from forest loss. Nature Geoscience. 2009;2:737-738. doi:10.1038/ngeo671.

Baccini

Goetz

Walker

Laporte

Sun

Sulla-Menashe

, et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon density maps. Nature Climate Change. 2012;2:182-185. doi:10.1038/nclimate1354.

Joint Research Centre/Netherlands Environmental Assessment Agency. Emissions Database for Global Atmospheric Research 4.0; 2009. Available at: http://edgar.jrc.ec.europa.eu.

10.

Forests of the World is an environmental NGO founded in Denmark. https://www.forestsoftheworld.org/programs/panama.

11.

Liu

Ekoungoulo

Loumeto

Ifo

Bocko

Koula

FE.

Evaluation of carbon stocks in above- and below-ground biomass in Central Africa: case study of Lesiolouna tropical rainforest of Congo. Biogeosciences Discuss. 2014;11:10703-10735. doi:10.5194/bgd-11-10703-2014.

12.

Lugo

Brown

Tropical forests as sinks of atmospheric carbon. Forest Ecol Manage. 1992;54:239-255. doi:10.1016/0378-1127(92)90016-3.

13.

Hedde

Aubert

Bureau

Margerie

Decaëns

Soil detritivore macro-invertebrate assemblages throughout a managed beech rotation. Ann Forest Sci. 2007;64:219-228. doi:10.1051/forest:2006106.

14.

Gorte

RW.

Carbon Sequestration in Forests (Report for Congress RL31432). Congressional Research Service;

2009. https://fas.org/sgp/crs/misc/RL31432.pdf.

15.

Benavides

RAM

Guerrero

Mateus

. Livestock greenhouse gas emissions under grazing conditions in the tropic. Revista Investigación Agraria Ambiental. 2019;10:91-106. doi:10.22490/21456453.2685.

16.

Crosby

Ford

Free

, et al. Carbon Sequestration and its Relationship to Forest Management and Biomass Harvesting in Vermont [Environmental Studies Senior Seminar (ES 401)]. Middlebury, VT: Middlebury College; 2010.

17.

Ahirwal

Maiti

. Chapter 21: carbon sequestration and soil CO2 flux in reclaimed coal mine lands from India. In: Bio-Geotechnologies for Mine Site Rehabilitation. Amsterdam, The Netherlands: Elsevier; 2018:371-392.

18.

Amundson

Biardeau

Opinion: soil carbon sequestration is an elusive climate mitigation tool. PNAS. 2018;115:11652-11656. doi:10.1073/pnas.1815901115.

19.

Cusack

Markesteijn

Condit

Lewis

Turner

BL.

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots. Biogeochemistry.2018;137:253. doi:10.1007/s10533-017-0416-8.

20.

Ryan

Law

. Interpreting, measuring, and modelling soil respiration. Biogeochemistry. 2005;73:3-27. doi:10.1007/s10533-004.

21.

Fang

Moncrieff

A model for soil CO2 production and transport 1: model development. Agricult Forest Meteorol. 1999;95:225-236.

22.

Eswaran

Van Den Berg

Reich

Organic carbon in soils of the world. Soil Sci Soc Am J. 1993;57:192-194.

23.

Novara

Pisciotta

Minacapilli

, et al. The impact of soil erosion on soil fertility and vine vigor: a multidisciplinary approach based on field, laboratory and remote sensing approaches. Sci Total Environ. 2017;622-623:474-480. doi:10.1016/j.scitotenv.2017.11.272.

24.

Scharlemann

JPW

Tanner

EVJ

Hiederer

Kapos

. Global soil carbon: understanding and managing the largest terrestrial carbon pool. Fut Sci. 2014;5:81-91. doi:10.4155/cmt.13.77.

25.

Grimm

Behrens

Märker

Elsenbeer

Soil organic carbon concentrations and stocks on Barro Colorado Island: digital soil mapping using random forest analysis. Geoderma. 2008;146:102-113. doi:10.1016/j.geoderma.2008.05.008.

26.

Dommergues

Belser

Schmidt

EL.

Limiting factors for microbial growth and activity in soil. Adv Microbial Ecol. 1977;2:49-104.

27.

Davidson

Trumbore

. Gas diffusivity and production of CO2 in deep soils of eastern Amazon. Tellus

. Chem Phys Meteorol. 1995;47:550-565. doi:10.3402/tellusb.v47i5.16071.

28.

Simunek

Suarez

DL.

Modelling of carbon dioxide transport and production in soil 1: model development. Water Resour Res. 1993;29:487-497.

29.

Fang

Moncrief

The dependence of soil CO2 efflux on temperature. Soil Biol Biochem. 2001;33:155-165. doi:10.1016/S0038-0717(00)00125.

30.

Silletta

Cavallaro

Kowal

, et al. Temporal and spatial variability in soil CO2 efflux in the Patagonian steppe. Plant Soil. 2019;444:165-176. doi:10.1007/s11104-019-04268-7.

31.

Altikat

Kucukerdem

Altikat

The response of CO2 flux to soil warming, manure application and soil salinity. J nst Sci Technol. 2019;9:1334-1342. doi:10.21597/jist.515501.

32.

Skog

Nicholson

. Carbon sequestration in wood and paper products. In: The Impact of Climate Change on America’s Forests: A Technical Document Supporting the 2000 USDA Forest Service RPA Assessment (Gen. Tech. Rept. RMRS-GTR-59). Fort Collins, CO: USDA Forest Service, Rocky Mountain Research Station; 2000:79-88.

33.

Rout

Gupta

SR.

Soil respiration in relation to abiotic factors, forest floor litter, root biomass and litter quality in forest ecosystems of Siwaliks in north India. Acta Oecologica. 1989;10:229-244. http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=7348630.

34.

LI-8100A. Automated Soil Gas Flux System: A Rugged System for Dependable Results, LI-COR Biosciences; 2019.

35.

Leigh

Rand

Windsor

DM.

The Ecology of a Tropical Forest: Seasonal Rhythms and Long-Term Change. 2nd ed. Washington, DC: Smithsonian Institution Press; 1996.

36.

Edwards

Reichle

Crossley

. The role of soil invertebrates in turnover of organic matter and nutrients. In: Reichle

(eds) Analysis of Temperate Forest Ecosystems. New York, NY: Springer-Verlag; 1970:12-172.

37.

Horwath

Pregitzer

Paul

EA.

14C allocation in tree-soil systems. Tree Physiol. 1994;14:1163-1176.

38.

Food and Agriculture Organization of the United Nations (FAO). World Reference Base for Soils. Rome, Italy: World Soil Resources Report 84; 1998.

39.

Leigh

Jr.

Tropical Forest Ecology: A View from Barro Colorado Island. 1st ed. Washington, DC: Smithsonian Institution Press; 1999.

40.

Woodring

Geology of Barro Colorado Island, Canal Zone. Washington, DC: Smithsonian Institution; 1958.

41.

Baillie

Elsenbeer

Barthold

Grimm

Stallard

Semi-Detailed Soil Survey of Barro Colorado Island, Panama. Washington, DC: Smithsonian Tropical Research Institute; 2017.

42.

Rubio

Detto

Spatiotemporal variability of soil respiration in a seasonal tropical forest. Ecol Evolut. 2017;7:7104-7116. doi:10.1002/ece3.3267.

43.

Albrecht

Stallard

Kalko

EKV

. Land use history and population dynamics of free-standing figs in a maturing forest. PLoS ONE. 2017;12:1-18. doi:10.1371/journal.pone.0177060.

44.

Bartlett

Barghoorn

Berger

Fossil maize from Panama. Science. 1969;151:642-643. doi:10.1126/science.165.3891.389.

45.

Bartlett

Barghoorn

. Phytogeographic history of the Isthmus of Panama during the past 12,000 years. In: Grahm

(ed.) Vegetation and Vegetational History of Northern Latin America. New York, NY: Elsevier. 1973:203-299.

46.

Foster

Brokaw

NVL

. Structure and history of the vegetation of Barro Colorado Island. In: Leigh

Rand

Windsor

(eds) The Ecology of a Tropical Forest: Seasonal Rhythms and Long-Term Change. 1st ed. Washington, DC: Smithsonian Institution Press; 1982:67-94.

47.

Kenoyer

LA.

General and successional ecology of the lower tropical rain-forest at Barro Colorado Island, Panama. Ecology. 1929;10:201-222.

48.

Navidi

Estadística para Ingenieros y Cientificos. Mexico City, Mexico: McGraw-Hill Interamericana Editores; 2006.

49.

Vinuesa

Tema 8: Correlación, Teoría y Práctica;

2016. http://www.ccg.unam.mx/~vinuesa/R4biosciences/docs/Tema8_correlacion_presentacionR.html#/.

50.

Canavos

Probabilidad y Estadística: Aplicaciones y Métodos. Mexico City, Mexico: McGraw-Hill Interamericana Editores; 1998.

51.

La Autoridad del Canal de Panamá (ACP). El Fenómeno del Niño y su Efecto en el Canal de Panamá. Panama City, Panama: Autoridad del Canal de Panamá, Vicepresidencia Ejecutiva de Agua, Ambiente y Energía; 2018.

52.

Empresa de Transmisión Eléctrica

S.A.

(ETESA)–HIDROMET, Probabilidades de Coincidencias Favorables para el Desarrollo del Niño en el Segundo Semestre del Año 2017. Gerencia de Investigación y Aplicaciones Climáticas; 2017.

53.

Kursar

TA.

Evaluation of soil respiration and soil CO2 concentration in a lowland moist forest in Panama. Plant Soil.1989;113:21-29. doi:10.1007/BF02181917.

54.

Vicca

Bahn

Estiarte

, et al. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments. Biogeosciences. 2014;11:2991-3013. doi:10.5194/bg-11-2991-2014.

55.

McDaniel

Kaye

Bruns

MA.

Climate change interactions affect soil carbon dioxide efflux and microbial functioning in a post harvest forest. Oecologia. 2013;174:1437-1448. doi:10.1007/s00442-013-2845-y.

56.

Shi

Qin

Liu

, et al. Soil respiration and response of carbon source changes to vegetation restoration in the Loess Plateau, China. Sci Total Environ. 2020;707:135507. doi:10.1016/j.scitotenv.2019.135507.

57.

Zhao

Pumpanen

Kang

Spatio-temporal variability and controls of soil respiration in a furrow-irrigated vineyard. Soil Tillage Res. 2020;196:104424. doi:10.1016/j.still.2019.104424.

58.

Chen

Wang

Zhang

Climatic, soil, and vegetation controls of the temperature sensitivity (Q10) of soil respiration across terrestrial biomes. Glob Ecol Conserv. 2020;22:e00955. doi:10.1016/j.gecco.2020.e00955.

59.

Rodrigo-Comino

Senciales

Cerdà

Brevik

EC.

The multidisciplinary origin of soil geography: a review. Earth Sci Rev. 2018;177:114-123. doi:10.1016/j.earscirev.2017.11.008.

60.

Brevik

Calzolari

Miller

, et al. Soil mapping, classification, and modeling: history and future directions. Geoderma. 2016;264:256-274. doi:10.1016/j.geoderma.2015.05.017.

61.

Bui

Stahr

Clemens

A fuzzy logic slope-form system for predictive soil mapping of a landscape-scale area with strong relief conditions. Catena. 2017;155:135-146. doi:10.1016/j.catena.2017.03.001.

62.

Oluwasinaayomi

Muluneh

Truphena

Bolanle

Land use and ambient air quality in Bahir Dar and Hawassa, Ethiopia. Air, Soil Water Res. 2018; 11:1-10. doi:10.1177/1178622117752138.

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First Approach of Abiotic Drivers of Soil CO 2 Efflux in Barro Colorado Island,Panama

Abstract

Keywords

Introduction

Materials and Methods

Study site

CO2 flux in soil

Soil temperature and humidity

Temperature

Humidity

Rainfall

Statistical analysis

Results

CO2 soil flux

Soil temperature

Soil humidity

Rainfall

Discussion

Conclusions

Footnotes

Acknowledgements

Funding:

Declaration of conflicting interests:

Author Contributions

ORCID iD

References

CO₂ flux in soil

CO₂ soil flux

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