A critical aspect of predicting soil organic carbon (SOC) concentrations is the lack of available soil information; where information on soil characteristics is available, it is usually focused on regions of high agricultural interest. To date, in Chile, a large proportion of the SOC data have been collected in areas of intensive agricultural or forestry use; however, vast areas beyond these forms of land use have few or no soil data available.
Here we present a new SOC database for the country, which is the result of
an unprecedented national effort under the framework of the Global Soil
Partnership. This partnership has helped build the largest database of SOC
to date in Chile, named the Chilean Soil Organic Carbon database (CHLSOC),
comprising 13 612 data points compiled from numerous sources, including
unpublished and difficult-to-access data. The database will allow users to
fill spatial gaps where no SOC estimates were publicly available previously.
Presented values of SOC range from
The database has the potential to inform and test current models that predict SOC stocks and dynamics at larger spatial scales, thus enabling benefits from the richness of geochemical, topographic and climatic variability in Chile.
The database is freely available to registered users at
Soil organic carbon (SOC) stocks play a vital role in the global carbon (C)
cycle and make up nearly two-thirds of the total terrestrial carbon pool
(Eswaran, 2000; Sarmiento and Gruber, 2002). Therefore, knowledge of the
contents and dynamics of SOC stocks is essential for estimating trends in
the evolution of atmospheric carbon dioxide (
Access to spatially explicit, consistent and reliable soil data is essential to model and map the status of soil resources globally to an increasingly detailed resolution in order to respond and assess global issues (Arrouays et al., 2014; FAO, 2015; Hengl et al., 2014; Omuto et al., 2013). Furthermore, soil datasets are one of the most important inputs for Earth system models (ESMs) to address, for example, the importance of terrestrial sinks and sources of greenhouse gases (Dai et al., 2019; Luo et al., 2016). At the same time, soils in ESMs are one of the largest sources of uncertainty (Dai et al., 2019). Hence, in recent years, there has been a growing effort to improve access to and quality of soil datasets, a key goal of the Global Soil Partnership Pillar 4 Implementation Plan sponsored by the Food and Agriculture Organization of the United Nations (Batjes et al., 2017; Omuto et al., 2013). Efforts to increase access to harmonized soil products containing comparable and consistent datasets, including soil carbon, are highly valuable and appreciated by an increasing number of users (Arora et al., 2013; Baritz et al., 2014; Batjes et al., 2017; Hendriks et al., 2016; Jones and Thornton, 2015; Luo et al., 2016; Maire et al., 2015).
In an unprecedented national effort, between May 2018 and April 2019, a group of professionals from 39 public and private institutions joined together to build the largest (to date) Chilean SOC database (CHLSOC). The database was compiled from varied data sources including soil surveys, publications, private reports, unpublished research data, and cryptic documents unknown to the public and often difficult to access. This work resulted in a harmonized database of 13 612 points, which is a great improvement considering that previously up-to-date harmonized data on SOC for Chile included 45 points in WoSIS (Batjes et al., 2017).
The entire CHLSOC database (13 612 data points from 25 sources; summarized in
Table 1) is freely available for registered users to download at
Database sources used in this compilation.
BLD: bulk density; WO: wet oxidation; DC: dry combustion; NA: data not provided; CIREN: Centro de Información de Recursos Naturales; INIA: Instituto de Investigaciones Agropecuarias; ODEPA: Oficina de Estudios y Políticas Agrarias; PUC: Pontificia Universidad Católica de Chile; SAG: Servicio Agrícola y Ganadero; SEIA: Sistema de Evaluación de Impacto Ambiental; UACH: Universidad Austral de Chile; UAP: Universidad Arturo Prat; UCB: University of California Berkeley; UChile: Universidad de Chile; UCT: Universidad Católica de Temuco; UDEC: Universidad de Concepción; UFRO: Universidad de la Frontera; UMAG: Universidad de Magallanes.
In order to fill the gaps in the current data, 889 soil profiles and 12 723 topsoil samples from all over Chile (Table 2) were gathered, curated and harmonized. Of this information, 89 % had previously been unpublished or unavailable to the national and global scientific community. The resultant soil information was from all of the administrative regions and 16 out of 17 ecological zones of Chile (Fig. 1; Table 3).
Summary of the soil points included in the Chilean Soil Organic Carbon database (CHLSOC).
SOC: soil organic carbon; BLD: bulk density; CRF: coarse fragments; topsoil
considers points with surface samples only
(
Distribution of SOC data points per ecosystem (vegetation formation) according to Luebert and Pliscoff (2006).
Percentages of surface area and English names for vegetation formations were taken from Pliscoff and Fuentes-Castillo (2011).
Data compiled from the literature are referenced in Table 1. Sources include
legacy soil surveys, environmental assessment reports, research papers,
private reports, theses and unpublished data provided by researchers. The
minimum requirements for inclusion in the database were geographic-coordinate information, records of soil horizon depth and soil organic
carbon content (or organic matter content). Other soil variables, such as
bulk density, texture and/or coarse fragments, sampling depth, sampling year,
and measurement methods, were included where available. Approximately 20 %
of horizon samples included information on bulk density (BLD) measured using
the clod or the core (cylinder) method, and only 382 horizons (
The resulting database (summarized in Table 1) includes datasets of variable size, source and composition. Unpublished data sources are referenced in the database to the co-author and group who provided the data. Examples of unpublished data sources are shown in Table 1 and include those of the Oficina de Estudios y Políticas Agrarias (ODEPA) with 782 points provided by José Ramirez, Methanobase (Table 1), corresponding to surface samples (0–25 cm) from the Magallanes Region collected in 2016 and provided by Lea Cabrol and Maialen Barret (Table 3). A further 51 data points from the Environmental Impact Assessment System (SEIA) were included from mostly underrepresented areas, such as the Andes and the Atacama Desert.
The largest contributor to CHLSOC (9935 data points) was the SOC dataset of the Agricultural and Livestock Service (SAG by its Spanish abbreviation). The data were comprised of SOC obtained from the first 20 cm of soil by auger or excavation methods sampled by beneficiaries (farmers) of the SAG subsidy program.
Another important data contributor was the legacy soil survey data compiled
by the Centro de Información de Recursos Naturales
(CIREN), reported as regional soil surveys that were carried out from the
1960s up to 2007. In total, CIREN compiled 37 soil surveys, totaling 540
data points over 177 500 km
The assembled data were sampled over several decades and compiled by different authors and institutions. We would like to mention the following warnings to the data users: first, for some data points it was not possible to find or verify the original data source. Second, a potential source of uncertainty may be the analytical method employed for analysis; for most samples (97 %), SOC content was analyzed using the wet-oxidation method, and a small number were analyzed by total combustion (CN elemental analyzer). Discrepancies in SOC results between combustion methods have identified wet combustion as a less reliable assessment method for SOC, as it tends to underestimate organic carbon at higher SOC contents (Kumar et al., 2019) and potentially overestimates it in highly reduced soils (Chatterjee et al., 2009). This issue has not been addressed in Chile to date. The recommended methods for SOC determination are currently wet oxidation and loss on ignition; however, dry combustion is a more accurate alternative (Sadzawka et al., 2006). Future data collection initiatives should stress consistent analytical procedures as a revision of local standards is urgently required. Finally, a possible source of bias in data from SAG is the fact that samples were taken by farmers following SAG guidelines where a composite sampling is taken for each parcel.
To date, CHLSOC is the most complete data compilation for mainland Chile, comprising 13 612 points, a great improvement in comparison with former databases used in Chile for SOC assessments. For example, national SOC mapping studies (Padarian et al., 2017; Reyes Rojas et al., 2018) were based almost exclusively on CIREN data (540 points). CHLSOC can be used to show the influence of soil, vegetation and climatic conditions on SOC concentrations. Table 3 shows the number of data compiled in this work, by vegetation formation. It is important to note that the scheme of Luebert and Pliscoff (2006) corresponds to the potential vegetation belts that originally occupied the territory and does not necessarily reflect current land use. We refer to vegetation formations as “ecosystems” as this is a more common term and to avoid further specific disciplinary discussion, which is outside the scope of this work. In order to represent each ecosystem (by vegetation formation) in CHLSOC, the database is based on the number of data points divided by the total coverage of the ecosystem in Chile.
More than two thirds (85.73 %) of the data are sampled from a concentrated
area (25 % of the total country area) found in the following four
ecosystems: deciduous forest, broad-leaved forest, sclerophyllous forest and
thorny forest. The first two ecosystems are located in the northern section
of the temperate macrobioclimatic zone and the second two in the southern
section of the Mediterranean macrobioclimatic zone (Moreira-Muñoz, 2011). These ecosystems are characterized by a combination of benign
climate, high-quality soils and water availability (for irrigation),
resulting in a long history of agricultural activity and human settlement
(Armesto et al., 2010). For this reason, these areas have experienced the
highest land use conversion to agriculture, forestry and urban use in the
country (Echeverría et al., 2006; Schulz et al., 2010; Arroyo et al.,
2008). Deciduous forests (14.7 % of the country) are the most represented,
with 52.14 % of the data points collected in CHLSOC located between
latitudes 35 and 41
The second-largest pool of data (8.6 % of the total data compiled in this
work) is for evergreen forest, steppe and grassland (Table 3), which
comprise 10.3 % of the country's area. These ecosystems are located
between 41 and 53
Spatial distribution of soil data points compiled in this work. Green triangles are soil profiles, and red squares are topsoil samples (up to 30 cm).
Arguably the most important ecosystem in terms of SOC stocks for Chile is
that of the moorlands, which comprise a large area located on the Pacific
coast of Patagonia where the landscape is fragmented into fjords and small
islands (between 44 and 55
The Atacama Desert section of Chile (Table 3; desert, low desert scrub and desertic scrub) comprises 2.18 % of the CHLSOC database but corresponds to 6 % of the country's area. However, the number of data points compiled for this region (298) constitutes a great improvement compared with previous national work on SOC for the Atacama Desert, which only included 3 points (Padarian et al., 2017).
The scarce SOC information for this region may be due to the extreme aridity of the region, low biological activity and low SOC accumulation (McKay et al., 2003). Vegetation is restricted to a narrow belt along the coast that receives water from fog, deep valleys that cross the desert and the western flank of the Andes (Moreira-Muñoz, 2011).
Regions of high altitude and mountainous areas comprise 102 data points
(0.74 % of the database) representing 16.2 % of the country's area. Two
characteristic alpine vegetation formations exist in the Chilean Andes between 18 and 38
Few data are available for the coniferous forest, deciduous shrubland, thorny shrubland and arborescent shrubland areas of vegetation (Table 3) located in areas of low forestry or agricultural interest, but these areas comprise less than 2.5 % of the country.
In summary, the data we have compiled demonstrate the imbalance between areas of agricultural and forestry interest and areas beyond those land uses. Three areas of high value in terms of ecological, scientific and ecosystem services nationwide (and worldwide) are underrepresented in terms of soil data: the high Andes, the Atacama Desert and western Patagonia. Government efforts to develop soil surveys in these regions should be promoted urgently. In particular, a SOC inventory of western Patagonia is essential to properly assess the national stock of SOC and the potential to include this area in carbon offset programs.
The date of sample collection is provided in more than 90 % of the included data (12 318 data points). The majority of points were sampled in 2006 and between 2010 and 2018 (Fig. 2). The high number of data from the last decade enables users to estimate modern carbon in Chilean soils. Most of the data that report the year in which they were sampled are concentrated in a short timeframe and mainly correspond to the SAG database (2010–2018) and to sampling efforts related to research projects such as ODEPA in 2006 and INIA (mainly 2015–2018).
Data from CIREN (Table 1) did not report a sampling date. However, as they consist of a compilation of known former soil surveys, we can limit the period in which samples were collected and analyzed to the period between 1970 and 2007. The oldest data points correspond to those collected by Holdgate (1961) in the western Patagonian fjords in 1959.
Temporal distribution of the samples included in CHLSOC.
Data are available at:
The process of generating this database was a distributed data collection effort, which is a step forward under the efforts of the GlobalSoilMap.net project and the guidelines of the FAO Global Soil Partnership. The database presented here increases the public availability of SOC data for Chile 10-fold thanks to a joint effort of dozens of researchers and institutions. A high proportion of this database, 89 % (12 125 data points), consists of unpublished data that have now been made available. CHLSOC now contains a valuable SOC representation of a mosaic of ecosystems in Chile which represents one of Earth's most extreme climate gradients. However, there are still big differences in the number of data obtained from managed (agro)ecosystems and natural systems in areas of low population density. We would like to stress the urgency of generating a discussion at a national level regarding the need for a comprehensive soil survey program to increase the sampling in these underrepresented areas. Moreover, to include more data in the next versions of CHLSOC, future official CIREN soil surveys in Chile and other datasets should be encouraged to report holistic metadata covering sampling designs, locations, sampling dates and analysis methods.
Naming conventions and descriptions of variables provided in the Chilean Soil Organic Carbon database (CHLSOC).
MP, GFO, MG, RO, NB, JB, MF, GG, AG, JM, JR, CR, IS and SB designed the framework to produce the database. The paper was written by MP and JP with contributions from all other authors, who reviewed and provided input on the paper.
The authors declare that they have no conflict of interest.
The following authors of unpublished data acknowledge funding from the following sources: Felipe Aburto, Fondecyt de Iniciación, grant no. 11160372, and Convenio CONAF–UDeC 2015 Perturbaciones Araucaria; Maialent Barret and Lea Cabrol, ERANet-LAC joint program, grant no. ELAC2014/DCC-0092; Erick Zagal and Cristina Muñoz, Proyecto Fondecyt, grant no. 1161492. Federico Olmedo and Mario Guevara were supported by the Global Soil Partnership and the South America Soil Partnership, both sponsored by the Food and Agriculture Organization of the United Nations (FAO).
There was no financial support for the publication of this paper.
This paper was edited by Giulio G. R. Iovine and reviewed by Sergey Zimov and three anonymous referees.